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extraction</title> <meta name="description" content="Search results for: feature extraction"> <meta name="keywords" content="feature extraction"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none 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action="https://publications.waset.org/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="feature extraction"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 1455</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: feature extraction</h1> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1455</span> Study of Features for Hand-printed Recognition</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Satish%20Kumar">Satish Kumar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The feature extraction method(s) used to recognize hand-printed characters play an important role in ICR applications. In order to achieve high recognition rate for a recognition system, the choice of a feature that suits for the given script is certainly an important task. Even if a new feature required to be designed for a given script, it is essential to know the recognition ability of the existing features for that script. Devanagari script is being used in various Indian languages besides Hindi the mother tongue of majority of Indians. This research examines a variety of feature extraction approaches, which have been used in various ICR/OCR applications, in context to Devanagari hand-printed script. The study is conducted theoretically and experimentally on more that 10 feature extraction methods. The various feature extraction methods have been evaluated on Devanagari hand-printed database comprising more than 25000 characters belonging to 43 alphabets. The recognition ability of the features have been evaluated using three classifiers i.e. k-NN, MLP and SVM. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Features" title="Features">Features</a>, <a href="https://publications.waset.org/search?q=Hand-printed" title=" Hand-printed"> Hand-printed</a>, <a href="https://publications.waset.org/search?q=Devanagari" title=" Devanagari"> Devanagari</a>, <a href="https://publications.waset.org/search?q=Classifier" title=" Classifier"> Classifier</a>, <a href="https://publications.waset.org/search?q=Database" title=" Database"> Database</a> </p> <a href="https://publications.waset.org/8497/study-of-features-for-hand-printed-recognition" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/8497/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/8497/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/8497/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/8497/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/8497/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/8497/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/8497/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/8497/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/8497/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/8497/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/8497.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1729</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1454</span> Development of a Semantic Wiki-based Feature Library for the Extraction of Manufacturing Feature and Manufacturing Information</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Hendry%20Muljadi">Hendry Muljadi</a>, <a href="https://publications.waset.org/search?q=Hideaki%20Takeda"> Hideaki Takeda</a>, <a href="https://publications.waset.org/search?q=Koichi%20Ando"> Koichi Ando</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A manufacturing feature can be defined simply as a geometric shape and its manufacturing information to create the shape. In a feature-based process planning system, feature library that consists of pre-defined manufacturing features and the manufacturing information to create the shape of the features, plays an important role in the extraction of manufacturing features with their proper manufacturing information. However, to manage the manufacturing information flexibly, it is important to build a feature library that can be easily modified. In this paper, the implementation of Semantic Wiki for the development of the feature library is proposed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Manufacturing%20feature" title="Manufacturing feature">Manufacturing feature</a>, <a href="https://publications.waset.org/search?q=feature%20library" title=" feature library"> feature library</a>, <a href="https://publications.waset.org/search?q=feature%0Aontology" title=" feature ontology"> feature ontology</a>, <a href="https://publications.waset.org/search?q=process%20planning" title=" process planning"> process planning</a>, <a href="https://publications.waset.org/search?q=Wiki" title=" Wiki"> Wiki</a>, <a href="https://publications.waset.org/search?q=MediaWiki" title=" MediaWiki"> MediaWiki</a>, <a href="https://publications.waset.org/search?q=Semantic%20Wiki." title=" Semantic Wiki."> Semantic Wiki.</a> </p> <a href="https://publications.waset.org/9813/development-of-a-semantic-wiki-based-feature-library-for-the-extraction-of-manufacturing-feature-and-manufacturing-information" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/9813/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/9813/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/9813/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/9813/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/9813/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/9813/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/9813/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/9813/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/9813/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/9813/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/9813.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1437</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1453</span> Myanmar Character Recognition Using Eight Direction Chain Code Frequency Features </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Kyi%20Pyar%20Zaw">Kyi Pyar Zaw</a>, <a href="https://publications.waset.org/search?q=Zin%20Mar%20Kyu"> Zin Mar Kyu </a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Character recognition is the process of converting a text image file into editable and searchable text file. Feature Extraction is the heart of any character recognition system. The character recognition rate may be low or high depending on the extracted features. In the proposed paper, 25 features for one character are used in character recognition. Basically, there are three steps of character recognition such as character segmentation, feature extraction and classification. In segmentation step, horizontal cropping method is used for line segmentation and vertical cropping method is used for character segmentation. In the Feature extraction step, features are extracted in two ways. The first way is that the 8 features are extracted from the entire input character using eight direction chain code frequency extraction. The second way is that the input character is divided into 16 blocks. For each block, although 8 feature values are obtained through eight-direction chain code frequency extraction method, we define the sum of these 8 feature values as a feature for one block. Therefore, 16 features are extracted from that 16 blocks in the second way. We use the number of holes feature to cluster the similar characters. We can recognize the almost Myanmar common characters with various font sizes by using these features. All these 25 features are used in both training part and testing part. In the classification step, the characters are classified by matching the all features of input character with already trained features of characters.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Chain%20code%20frequency" title="Chain code frequency">Chain code frequency</a>, <a href="https://publications.waset.org/search?q=character%20recognition" title=" character recognition"> character recognition</a>, <a href="https://publications.waset.org/search?q=feature%20extraction" title=" feature extraction"> feature extraction</a>, <a href="https://publications.waset.org/search?q=features%20matching" title=" features matching"> features matching</a>, <a href="https://publications.waset.org/search?q=segmentation." title=" segmentation."> segmentation.</a> </p> <a href="https://publications.waset.org/10009080/myanmar-character-recognition-using-eight-direction-chain-code-frequency-features" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10009080/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10009080/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10009080/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10009080/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10009080/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10009080/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10009080/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10009080/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10009080/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10009080/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10009080.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">753</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1452</span> Scale-Space Volume Descriptors for Automatic 3D Facial Feature Extraction</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Daniel%20Chen">Daniel Chen</a>, <a href="https://publications.waset.org/search?q=George%20Mamic"> George Mamic</a>, <a href="https://publications.waset.org/search?q=Clinton%20Fookes"> Clinton Fookes</a>, <a href="https://publications.waset.org/search?q=Sridha%20Sridharan"> Sridha Sridharan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>An automatic method for the extraction of feature points for face based applications is proposed. The system is based upon volumetric feature descriptors, which in this paper has been extended to incorporate scale space. The method is robust to noise and has the ability to extract local and holistic features simultaneously from faces stored in a database. Extracted features are stable over a range of faces, with results indicating that in terms of intra-ID variability, the technique has the ability to outperform manual landmarking.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Scale%20space%20volume%20descriptor" title="Scale space volume descriptor">Scale space volume descriptor</a>, <a href="https://publications.waset.org/search?q=feature%20extraction" title=" feature extraction"> feature extraction</a>, <a href="https://publications.waset.org/search?q=3D%20facial%20landmarking" title=" 3D facial landmarking"> 3D facial landmarking</a> </p> <a href="https://publications.waset.org/1712/scale-space-volume-descriptors-for-automatic-3d-facial-feature-extraction" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/1712/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/1712/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/1712/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/1712/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/1712/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/1712/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/1712/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/1712/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/1712/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/1712/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/1712.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1508</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1451</span> Motion Recognition Based On Fuzzy WP Feature Extraction Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Keun-Chang%20Kwak">Keun-Chang Kwak</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>This paper is concerned with motion recognition based fuzzy WP(Wavelet Packet) feature extraction approach from Vicon physical data sets. For this purpose, we use an efficient fuzzy mutual-information-based WP transform for feature extraction. This method estimates the required mutual information using a novel approach based on fuzzy membership function. The physical action data set includes 10 normal and 10 aggressive physical actions that measure the human activity. The data have been collected from 10 subjects using the Vicon 3D tracker. The experiments consist of running, seating, and walking as physical activity motion among various activities. The experimental results revealed that the presented feature extraction approach showed good recognition performance.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Motion%20recognition" title="Motion recognition">Motion recognition</a>, <a href="https://publications.waset.org/search?q=fuzzy%20wavelet%20packet" title=" fuzzy wavelet packet"> fuzzy wavelet packet</a>, <a href="https://publications.waset.org/search?q=Vicon%0D%0Aphysical%20data." title=" Vicon physical data."> Vicon physical data.</a> </p> <a href="https://publications.waset.org/4617/motion-recognition-based-on-fuzzy-wp-feature-extraction-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/4617/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/4617/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/4617/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/4617/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/4617/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/4617/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/4617/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/4617/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/4617/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/4617/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/4617.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1644</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1450</span> Walsh-Hadamard Transform for Facial Feature Extraction in Face Recognition</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=M.%20Hassan">M. Hassan</a>, <a href="https://publications.waset.org/search?q=I.%20Osman"> I. Osman</a>, <a href="https://publications.waset.org/search?q=M.%20Yahia"> M. Yahia</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>This Paper proposes a new facial feature extraction approach, Wash-Hadamard Transform (WHT). This approach is based on correlation between local pixels of the face image. Its primary advantage is the simplicity of its computation. The paper compares the proposed approach, WHT, which was traditionally used in data compression with two other known approaches: the Principal Component Analysis (PCA) and the Discrete Cosine Transform (DCT) using the face database of Olivetti Research Laboratory (ORL). In spite of its simple computation, the proposed algorithm (WHT) gave very close results to those obtained by the PCA and DCT. This paper initiates the research into WHT and the family of frequency transforms and examines their suitability for feature extraction in face recognition applications.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Face%20Recognition" title="Face Recognition">Face Recognition</a>, <a href="https://publications.waset.org/search?q=Facial%20Feature%20Extraction" title=" Facial Feature Extraction"> Facial Feature Extraction</a>, <a href="https://publications.waset.org/search?q=Principal%20Component%20Analysis" title=" Principal Component Analysis"> Principal Component Analysis</a>, <a href="https://publications.waset.org/search?q=and%20Discrete%20Cosine%20Transform" title=" and Discrete Cosine Transform"> and Discrete Cosine Transform</a>, <a href="https://publications.waset.org/search?q=Wash-Hadamard%20Transform." title=" Wash-Hadamard Transform."> Wash-Hadamard Transform.</a> </p> <a href="https://publications.waset.org/2475/walsh-hadamard-transform-for-facial-feature-extraction-in-face-recognition" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/2475/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/2475/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/2475/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/2475/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/2475/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/2475/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/2475/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/2475/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/2475/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/2475/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/2475.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">2571</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1449</span> Feature Reduction of Nearest Neighbor Classifiers using Genetic Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=M.%20Analoui">M. Analoui</a>, <a href="https://publications.waset.org/search?q=M.%20Fadavi%20Amiri"> M. Fadavi Amiri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The design of a pattern classifier includes an attempt to select, among a set of possible features, a minimum subset of weakly correlated features that better discriminate the pattern classes. This is usually a difficult task in practice, normally requiring the application of heuristic knowledge about the specific problem domain. The selection and quality of the features representing each pattern have a considerable bearing on the success of subsequent pattern classification. Feature extraction is the process of deriving new features from the original features in order to reduce the cost of feature measurement, increase classifier efficiency, and allow higher classification accuracy. Many current feature extraction techniques involve linear transformations of the original pattern vectors to new vectors of lower dimensionality. While this is useful for data visualization and increasing classification efficiency, it does not necessarily reduce the number of features that must be measured since each new feature may be a linear combination of all of the features in the original pattern vector. In this paper a new approach is presented to feature extraction in which feature selection, feature extraction, and classifier training are performed simultaneously using a genetic algorithm. In this approach each feature value is first normalized by a linear equation, then scaled by the associated weight prior to training, testing, and classification. A knn classifier is used to evaluate each set of feature weights. The genetic algorithm optimizes a vector of feature weights, which are used to scale the individual features in the original pattern vectors in either a linear or a nonlinear fashion. By this approach, the number of features used in classifying can be finely reduced. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Feature%20reduction" title="Feature reduction">Feature reduction</a>, <a href="https://publications.waset.org/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/search?q=pattern%0Aclassification" title=" pattern classification"> pattern classification</a>, <a href="https://publications.waset.org/search?q=nearest%20neighbor%20rule%20classifiers%20%28k-NNR%29." title=" nearest neighbor rule classifiers (k-NNR)."> nearest neighbor rule classifiers (k-NNR).</a> </p> <a href="https://publications.waset.org/6432/feature-reduction-of-nearest-neighbor-classifiers-using-genetic-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/6432/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/6432/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/6432/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/6432/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/6432/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/6432/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/6432/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/6432/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/6432/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/6432/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/6432.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1767</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1448</span> Development of a Wiki-based Feature Library for a Process Planning System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Hendry%20Muljadi">Hendry Muljadi</a>, <a href="https://publications.waset.org/search?q=Hideaki%20Takeda"> Hideaki Takeda</a>, <a href="https://publications.waset.org/search?q=Koichi%20Ando"> Koichi Ando</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A manufacturing feature can be defined simply as a geometric shape and its manufacturing information to create the shape. In a feature-based process planning system, feature library plays an important role in the extraction of manufacturing features with their proper manufacturing information. However, to manage the manufacturing information flexibly, it is important to build a feature library that is easy to modify. In this paper, a Wiki-based feature library is proposed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Manufacturing%20feature" title="Manufacturing feature">Manufacturing feature</a>, <a href="https://publications.waset.org/search?q=feature%20library" title=" feature library"> feature library</a>, <a href="https://publications.waset.org/search?q=feature%0Aontology" title=" feature ontology"> feature ontology</a>, <a href="https://publications.waset.org/search?q=process%20planning" title=" process planning"> process planning</a>, <a href="https://publications.waset.org/search?q=Wiki" title=" Wiki"> Wiki</a>, <a href="https://publications.waset.org/search?q=MediaWiki." title=" MediaWiki."> MediaWiki.</a> </p> <a href="https://publications.waset.org/11944/development-of-a-wiki-based-feature-library-for-a-process-planning-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/11944/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/11944/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/11944/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/11944/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/11944/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/11944/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/11944/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/11944/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/11944/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/11944/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/11944.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1418</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1447</span> Wavelet and K-L Seperability Based Feature Extraction Method for Functional Data Classification</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Jun%20Wan">Jun Wan</a>, <a href="https://publications.waset.org/search?q=Zehua%20Chen"> Zehua Chen</a>, <a href="https://publications.waset.org/search?q=Yingwu%20Chen"> Yingwu Chen</a>, <a href="https://publications.waset.org/search?q=Zhidong%20Bai"> Zhidong Bai</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper proposes a novel feature extraction method, based on Discrete Wavelet Transform (DWT) and K-L Seperability (KLS), for the classification of Functional Data (FD). This method combines the decorrelation and reduction property of DWT and the additive independence property of KLS, which is helpful to extraction classification features of FD. It is an advanced approach of the popular wavelet based shrinkage method for functional data reduction and classification. A theory analysis is given in the paper to prove the consistent convergence property, and a simulation study is also done to compare the proposed method with the former shrinkage ones. The experiment results show that this method has advantages in improving classification efficiency, precision and robustness. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=classification" title="classification">classification</a>, <a href="https://publications.waset.org/search?q=functional%20data" title=" functional data"> functional data</a>, <a href="https://publications.waset.org/search?q=feature%20extraction" title=" feature extraction"> feature extraction</a>, <a href="https://publications.waset.org/search?q=K-Lseperability" title=" K-Lseperability"> K-Lseperability</a>, <a href="https://publications.waset.org/search?q=wavelet." title=" wavelet."> wavelet.</a> </p> <a href="https://publications.waset.org/6083/wavelet-and-k-l-seperability-based-feature-extraction-method-for-functional-data-classification" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/6083/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/6083/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/6083/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/6083/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/6083/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/6083/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/6083/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/6083/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/6083/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/6083/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/6083.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1466</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1446</span> An Automatic Feature Extraction Technique for 2D Punch Shapes</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Awais%20Ahmad%20Khan">Awais Ahmad Khan</a>, <a href="https://publications.waset.org/search?q=Emad%20Abouel%20Nasr"> Emad Abouel Nasr</a>, <a href="https://publications.waset.org/search?q=H.%20M.%20A.%20Hussein"> H. M. A. Hussein</a>, <a href="https://publications.waset.org/search?q=Abdulrahman%20Al-Ahmari"> Abdulrahman Al-Ahmari</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Sheet-metal parts have been widely applied in electronics, communication and mechanical industries in recent decades; but the advancement in sheet-metal part design and manufacturing is still behind in comparison with the increasing importance of sheet-metal parts in modern industry. This paper presents a methodology for automatic extraction of some common 2D internal sheet metal features. The features used in this study are taken from Unipunch ™ catalogue. The extraction process starts with the data extraction from STEP file using an object oriented approach and with the application of suitable algorithms and rules, all features contained in the catalogue are automatically extracted. Since the extracted features include geometry and engineering information, they will be effective for downstream application such as feature rebuilding and process planning.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Feature%20Extraction" title="Feature Extraction">Feature Extraction</a>, <a href="https://publications.waset.org/search?q=Internal%20Features" title=" Internal Features"> Internal Features</a>, <a href="https://publications.waset.org/search?q=Punch%20Shapes" title=" Punch Shapes"> Punch Shapes</a>, <a href="https://publications.waset.org/search?q=Sheet%20metal" title=" Sheet metal"> Sheet metal</a>, <a href="https://publications.waset.org/search?q=STEP." title=" STEP."> STEP.</a> </p> <a href="https://publications.waset.org/10004369/an-automatic-feature-extraction-technique-for-2d-punch-shapes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10004369/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10004369/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10004369/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10004369/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10004369/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10004369/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10004369/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10004369/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10004369/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10004369/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10004369.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">2092</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1445</span> Texture Feature Extraction using Slant-Hadamard Transform</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=M.%20J.%20Nassiri">M. J. Nassiri</a>, <a href="https://publications.waset.org/search?q=A.%20Vafaei"> A. Vafaei</a>, <a href="https://publications.waset.org/search?q=A.%20Monadjemi"> A. Monadjemi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Random and natural textures classification is still one of the biggest challenges in the field of image processing and pattern recognition. In this paper, texture feature extraction using Slant Hadamard Transform was studied and compared to other signal processing-based texture classification schemes. A parametric SHT was also introduced and employed for natural textures feature extraction. We showed that a subtly modified parametric SHT can outperform ordinary Walsh-Hadamard transform and discrete cosine transform. Experiments were carried out on a subset of Vistex random natural texture images using a kNN classifier. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Texture%20Analysis" title="Texture Analysis">Texture Analysis</a>, <a href="https://publications.waset.org/search?q=Slant%20Transform" title=" Slant Transform"> Slant Transform</a>, <a href="https://publications.waset.org/search?q=Hadamard" title=" Hadamard"> Hadamard</a>, <a href="https://publications.waset.org/search?q=DCT." title=" DCT."> DCT.</a> </p> <a href="https://publications.waset.org/11092/texture-feature-extraction-using-slant-hadamard-transform" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/11092/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/11092/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/11092/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/11092/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/11092/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/11092/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/11092/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/11092/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/11092/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/11092/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/11092.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">2673</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1444</span> Automatic Extraction of Water Bodies Using Whole-R Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Nikhat%20Nawaz">Nikhat Nawaz</a>, <a href="https://publications.waset.org/search?q=S.%20Srinivasulu"> S. Srinivasulu</a>, <a href="https://publications.waset.org/search?q=P.%20Kesava%20Rao"> P. Kesava Rao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Feature extraction plays an important role in many remote sensing applications. Automatic extraction of water bodies is of great significance in many remote sensing applications like change detection, image retrieval etc. This paper presents a procedure for automatic extraction of water information from remote sensing images. The algorithm uses the relative location of R color component of the chromaticity diagram. This method is then integrated with the effectiveness of the spatial scale transformation of whole method. The whole method is based on water index fitted from spectral library. Experimental results demonstrate the improved accuracy and effectiveness of the integrated method for automatic extraction of water bodies.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Chromaticity" title="Chromaticity">Chromaticity</a>, <a href="https://publications.waset.org/search?q=Feature%20Extraction" title=" Feature Extraction"> Feature Extraction</a>, <a href="https://publications.waset.org/search?q=Remote%20Sensing" title=" Remote Sensing"> Remote Sensing</a>, <a href="https://publications.waset.org/search?q=Spectral%20library" title=" Spectral library"> Spectral library</a>, <a href="https://publications.waset.org/search?q=Water%20Index." title=" Water Index."> Water Index.</a> </p> <a href="https://publications.waset.org/9996774/automatic-extraction-of-water-bodies-using-whole-r-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/9996774/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/9996774/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/9996774/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/9996774/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/9996774/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/9996774/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/9996774/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/9996774/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/9996774/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/9996774/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/9996774.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">3370</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1443</span> Enhancing capabilities of Texture Extraction for Color Image Retrieval</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Pranam%20Janney">Pranam Janney</a>, <a href="https://publications.waset.org/search?q=Sridhar%20G"> Sridhar G</a>, <a href="https://publications.waset.org/search?q=Sridhar%20V."> Sridhar V.</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Content-Based Image Retrieval has been a major area of research in recent years. Efficient image retrieval with high precision would require an approach which combines usage of both the color and texture features of the image. In this paper we propose a method for enhancing the capabilities of texture based feature extraction and further demonstrate the use of these enhanced texture features in Texture-Based Color Image Retrieval. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Image%20retrieval" title="Image retrieval">Image retrieval</a>, <a href="https://publications.waset.org/search?q=texture%20feature%20extraction" title=" texture feature extraction"> texture feature extraction</a>, <a href="https://publications.waset.org/search?q=color%0Aextraction" title=" color extraction"> color extraction</a> </p> <a href="https://publications.waset.org/12008/enhancing-capabilities-of-texture-extraction-for-color-image-retrieval" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/12008/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/12008/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/12008/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/12008/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/12008/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/12008/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/12008/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/12008/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/12008/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/12008/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/12008.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1622</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1442</span> Generic Multimedia Database Architecture</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Mohib%20ur%20Rehman">Mohib ur Rehman</a>, <a href="https://publications.waset.org/search?q=Imran%20Ihsan"> Imran Ihsan</a>, <a href="https://publications.waset.org/search?q=Mobin%20Uddin%20Ahmed"> Mobin Uddin Ahmed</a>, <a href="https://publications.waset.org/search?q=Nadeem%20Iftikhar"> Nadeem Iftikhar</a>, <a href="https://publications.waset.org/search?q=Muhammad%20Abdul%20Qadir"> Muhammad Abdul Qadir</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Multimedia, as it stands now is perhaps the most diverse and rich culture around the globe. One of the major needs of Multimedia is to have a single system that enables people to efficiently search through their multimedia catalogues. Many Domain Specific Systems and architectures have been proposed but up till now no generic and complete architecture is proposed. In this paper, we have suggested a generic architecture for Multimedia Database. The main strengths of our architecture besides being generic are Semantic Libraries to reduce semantic gap, levels of feature extraction for more specific and detailed feature extraction according to classes defined by prior level, and merging of two types of queries i.e. text and QBE (Query by Example) for more accurate yet detailed results. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Multimedia%20Database%20Architecture" title="Multimedia Database Architecture">Multimedia Database Architecture</a>, <a href="https://publications.waset.org/search?q=Semantics" title=" Semantics"> Semantics</a>, <a href="https://publications.waset.org/search?q=Feature%20Extraction" title="Feature Extraction">Feature Extraction</a>, <a href="https://publications.waset.org/search?q=Ontology." title=" Ontology."> Ontology.</a> </p> <a href="https://publications.waset.org/8121/generic-multimedia-database-architecture" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/8121/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/8121/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/8121/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/8121/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/8121/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/8121/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/8121/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/8121/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/8121/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/8121/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/8121.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1794</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1441</span> Analysis of Feature Space for a 2d/3d Vision based Emotion Recognition Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Robert%20Niese">Robert Niese</a>, <a href="https://publications.waset.org/search?q=Ayoub%20Al-Hamadi"> Ayoub Al-Hamadi</a>, <a href="https://publications.waset.org/search?q=Bernd%20Michaelis"> Bernd Michaelis</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In modern human computer interaction systems (HCI), emotion recognition is becoming an imperative characteristic. The quest for effective and reliable emotion recognition in HCI has resulted in a need for better face detection, feature extraction and classification. In this paper we present results of feature space analysis after briefly explaining our fully automatic vision based emotion recognition method. We demonstrate the compactness of the feature space and show how the 2d/3d based method achieves superior features for the purpose of emotion classification. Also it is exposed that through feature normalization a widely person independent feature space is created. As a consequence, the classifier architecture has only a minor influence on the classification result. This is particularly elucidated with the help of confusion matrices. For this purpose advanced classification algorithms, such as Support Vector Machines and Artificial Neural Networks are employed, as well as the simple k- Nearest Neighbor classifier. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Facial%20expression%20analysis" title="Facial expression analysis">Facial expression analysis</a>, <a href="https://publications.waset.org/search?q=Feature%20extraction" title=" Feature extraction"> Feature extraction</a>, <a href="https://publications.waset.org/search?q=Image%20processing" title=" Image processing"> Image processing</a>, <a href="https://publications.waset.org/search?q=Pattern%20Recognition" title=" Pattern Recognition"> Pattern Recognition</a>, <a href="https://publications.waset.org/search?q=Application." title=" Application."> Application.</a> </p> <a href="https://publications.waset.org/4039/analysis-of-feature-space-for-a-2d3d-vision-based-emotion-recognition-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/4039/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/4039/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/4039/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/4039/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/4039/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/4039/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/4039/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/4039/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/4039/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/4039/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/4039.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1923</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1440</span> Road Extraction Using Stationary Wavelet Transform</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Somkait%20Udomhunsakul"> Somkait Udomhunsakul</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>In this paper, a novel road extraction method using Stationary Wavelet Transform is proposed. To detect road features from color aerial satellite imagery, Mexican hat Wavelet filters are used by applying the Stationary Wavelet Transform in a multiresolution, multi-scale, sense and forming the products of Wavelet coefficients at a different scales to locate and identify road features at a few scales. In addition, the shifting of road features locations is considered through multiple scales for robust road extraction in the asymmetry road feature profiles. From the experimental results, the proposed method leads to a useful technique to form the basis of road feature extraction. Also, the method is general and can be applied to other features in imagery.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Road%20extraction" title=" Road extraction"> Road extraction</a>, <a href="https://publications.waset.org/search?q=Multiresolution" title=" Multiresolution"> Multiresolution</a>, <a href="https://publications.waset.org/search?q=Stationary%20Wavelet%20Transform" title=" Stationary Wavelet Transform"> Stationary Wavelet Transform</a>, <a href="https://publications.waset.org/search?q=Multi-scale%20analysis" title=" Multi-scale analysis"> Multi-scale analysis</a> </p> <a href="https://publications.waset.org/16132/road-extraction-using-stationary-wavelet-transform" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/16132/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/16132/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/16132/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/16132/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/16132/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/16132/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/16132/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/16132/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/16132/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/16132/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/16132.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1877</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1439</span> A Communication Signal Recognition Algorithm Based on Holder Coefficient Characteristics</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Hui%20Zhang">Hui Zhang</a>, <a href="https://publications.waset.org/search?q=Ye%20Tian"> Ye Tian</a>, <a href="https://publications.waset.org/search?q=Fang%20Ye"> Fang Ye</a>, <a href="https://publications.waset.org/search?q=Ziming%20Guo"> Ziming Guo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Communication signal modulation recognition technology is one of the key technologies in the field of modern information warfare. At present, communication signal automatic modulation recognition methods are mainly divided into two major categories. One is the maximum likelihood hypothesis testing method based on decision theory, the other is a statistical pattern recognition method based on feature extraction. Now, the most commonly used is a statistical pattern recognition method, which includes feature extraction and classifier design. With the increasingly complex electromagnetic environment of communications, how to effectively extract the features of various signals at low signal-to-noise ratio (SNR) is a hot topic for scholars in various countries. To solve this problem, this paper proposes a feature extraction algorithm for the communication signal based on the improved Holder cloud feature. And the extreme learning machine (ELM) is used which aims at the problem of the real-time in the modern warfare to classify the extracted features. The algorithm extracts the digital features of the improved cloud model without deterministic information in a low SNR environment, and uses the improved cloud model to obtain more stable Holder cloud features and the performance of the algorithm is improved. This algorithm addresses the problem that a simple feature extraction algorithm based on Holder coefficient feature is difficult to recognize at low SNR, and it also has a better recognition accuracy. The results of simulations show that the approach in this paper still has a good classification result at low SNR, even when the SNR is -15dB, the recognition accuracy still reaches 76%. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Communication%20signal" title="Communication signal">Communication signal</a>, <a href="https://publications.waset.org/search?q=feature%20extraction" title=" feature extraction"> feature extraction</a>, <a href="https://publications.waset.org/search?q=holder%0D%0Acoefficient" title=" holder coefficient"> holder coefficient</a>, <a href="https://publications.waset.org/search?q=improved%20cloud%20model." title=" improved cloud model."> improved cloud model.</a> </p> <a href="https://publications.waset.org/10010432/a-communication-signal-recognition-algorithm-based-on-holder-coefficient-characteristics" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10010432/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10010432/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10010432/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10010432/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10010432/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10010432/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10010432/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10010432/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10010432/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10010432/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10010432.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">708</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1438</span> Prediction of Cardiovascular Disease by Applying Feature Extraction</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Nebi%20Gedik">Nebi Gedik</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Heart disease threatens the lives of a great number of people every year around the world. Heart issues lead to many of all deaths; therefore, early diagnosis and treatment are critical. The diagnosis of heart disease is complicated due to several factors affecting health such as high blood pressure, raised cholesterol, an irregular pulse rhythm, and more. Artificial intelligence has the potential to assist in the early detection and treatment of diseases. Improving heart failure prediction is one of the primary goals of research on heart disease risk assessment. This study aims to determine the features that provide the most successful classification prediction in detecting cardiovascular disease. The performances of each feature are compared using the K-Nearest Neighbor machine learning method. The feature that gives the most successful performance has been identified.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Cardiovascular%20disease" title="Cardiovascular disease">Cardiovascular disease</a>, <a href="https://publications.waset.org/search?q=feature%20extraction" title=" feature extraction"> feature extraction</a>, <a href="https://publications.waset.org/search?q=supervised%20learning" title=" supervised learning"> supervised learning</a>, <a href="https://publications.waset.org/search?q=k-NN." title=" k-NN."> k-NN.</a> </p> <a href="https://publications.waset.org/10013584/prediction-of-cardiovascular-disease-by-applying-feature-extraction" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10013584/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10013584/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10013584/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10013584/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10013584/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10013584/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10013584/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10013584/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10013584/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10013584/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10013584.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">134</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1437</span> Ottoman Script Recognition Using Hidden Markov Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Ay%C5%9Fe%20Onat">Ay艧e Onat</a>, <a href="https://publications.waset.org/search?q=Ferruh%20Yildiz"> Ferruh Yildiz</a>, <a href="https://publications.waset.org/search?q=Mesut%20G%C3%BCnd%C3%BCz"> Mesut G眉nd眉z</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, an OCR system for segmentation, feature extraction and recognition of Ottoman Scripts has been developed using handwritten characters. Detection of handwritten characters written by humans is a difficult process. Segmentation and feature extraction stages are based on geometrical feature analysis, followed by the chain code transformation of the main strokes of each character. The output of segmentation is well-defined segments that can be fed into any classification approach. The classes of main strokes are identified through left-right Hidden Markov Model (HMM). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Chain%20Code" title="Chain Code">Chain Code</a>, <a href="https://publications.waset.org/search?q=HMM" title=" HMM"> HMM</a>, <a href="https://publications.waset.org/search?q=Ottoman%20Script%20Recognition" title=" Ottoman Script Recognition"> Ottoman Script Recognition</a>, <a href="https://publications.waset.org/search?q=OCR" title="OCR">OCR</a> </p> <a href="https://publications.waset.org/4689/ottoman-script-recognition-using-hidden-markov-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/4689/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/4689/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/4689/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/4689/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/4689/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/4689/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/4689/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/4689/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/4689/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/4689/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/4689.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">2319</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1436</span> Face Recognition Using Morphological Shared-weight Neural Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Hossein%20Sahoolizadeh">Hossein Sahoolizadeh</a>, <a href="https://publications.waset.org/search?q=Mahdi%20Rahimi"> Mahdi Rahimi</a>, <a href="https://publications.waset.org/search?q=Hamid%20Dehghani"> Hamid Dehghani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We introduce an algorithm based on the morphological shared-weight neural network. Being nonlinear and translation-invariant, the MSNN can be used to create better generalization during face recognition. Feature extraction is performed on grayscale images using hit-miss transforms that are independent of gray-level shifts. The output is then learned by interacting with the classification process. The feature extraction and classification networks are trained together, allowing the MSNN to simultaneously learn feature extraction and classification for a face. For evaluation, we test for robustness under variations in gray levels and noise while varying the network-s configuration to optimize recognition efficiency and processing time. Results show that the MSNN performs better for grayscale image pattern classification than ordinary neural networks. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Face%20recognition" title="Face recognition">Face recognition</a>, <a href="https://publications.waset.org/search?q=Neural%20Networks" title=" Neural Networks"> Neural Networks</a>, <a href="https://publications.waset.org/search?q=Multi-layer%0APerceptron" title=" Multi-layer Perceptron"> Multi-layer Perceptron</a>, <a href="https://publications.waset.org/search?q=masking." title=" masking."> masking.</a> </p> <a href="https://publications.waset.org/8627/face-recognition-using-morphological-shared-weight-neural-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/8627/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/8627/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/8627/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/8627/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/8627/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/8627/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/8627/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/8627/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/8627/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/8627/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/8627.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1516</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1435</span> Human Detection using Projected Edge Feature</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Jaedo%20Kim">Jaedo Kim</a>, <a href="https://publications.waset.org/search?q=Youngjoon%20Han"> Youngjoon Han</a>, <a href="https://publications.waset.org/search?q=Hernsoo%20Hahn"> Hernsoo Hahn</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The purpose of this paper is to detect human in images. This paper proposes a method for extracting human body feature descriptors consisting of projected edge component series. The feature descriptor can express appearances and shapes of human with local and global distribution of edges. Our method evaluated with a linear SVM classifier on Daimler-Chrysler pedestrian dataset, and test with various sub-region size. The result shows that the accuracy level of proposed method similar to Histogram of Oriented Gradients(HOG) feature descriptor and feature extraction process is simple and faster than existing methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Human%20detection" title="Human detection">Human detection</a>, <a href="https://publications.waset.org/search?q=Projected%20edge%20descriptor" title=" Projected edge descriptor"> Projected edge descriptor</a>, <a href="https://publications.waset.org/search?q=Linear%20SVM" title=" Linear SVM"> Linear SVM</a>, <a href="https://publications.waset.org/search?q=Local%20appearance%20feature" title=" Local appearance feature"> Local appearance feature</a> </p> <a href="https://publications.waset.org/7698/human-detection-using-projected-edge-feature" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/7698/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/7698/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/7698/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/7698/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/7698/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/7698/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/7698/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/7698/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/7698/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/7698/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/7698.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1500</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1434</span> Feature's Extraction of Human Body Composition in Images by Segmentation Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Mousa%20Mojarrad">Mousa Mojarrad</a>, <a href="https://publications.waset.org/search?q=Mashallah%20Abbasi%20Dezfouli"> Mashallah Abbasi Dezfouli</a>, <a href="https://publications.waset.org/search?q=Amir%20Masoud%20Rahmani"> Amir Masoud Rahmani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Detection and recognition of the Human Body Composition and extraction their measures (width and length of human body) in images are a major issue in detecting objects and the important field in Image, Signal and Vision Computing in recent years. Finding people and extraction their features in Images are particularly important problem of object recognition, because people can have high variability in the appearance. This variability may be due to the configuration of a person (e.g., standing vs. sitting vs. jogging), the pose (e.g. frontal vs. lateral view), clothing, and variations in illumination. In this study, first, Human Body is being recognized in image then the measures of Human Body extract from the image.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Analysis%20of%20image%20processing" title="Analysis of image processing">Analysis of image processing</a>, <a href="https://publications.waset.org/search?q=canny%20edge%20detection" title=" canny edge detection"> canny edge detection</a>, <a href="https://publications.waset.org/search?q=classification" title=" classification"> classification</a>, <a href="https://publications.waset.org/search?q=feature%20extraction" title=" feature extraction"> feature extraction</a>, <a href="https://publications.waset.org/search?q=human%20body%20recognition" title=" human body recognition"> human body recognition</a>, <a href="https://publications.waset.org/search?q=segmentation." title=" segmentation."> segmentation.</a> </p> <a href="https://publications.waset.org/8257/features-extraction-of-human-body-composition-in-images-by-segmentation-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/8257/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/8257/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/8257/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/8257/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/8257/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/8257/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/8257/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/8257/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/8257/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/8257/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/8257.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">2771</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1433</span> Statistical Feature Extraction Method for Wood Species Recognition System </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Mohd%20Iz%27aan%20Paiz%20Bin%20Zamri">Mohd Iz'aan Paiz Bin Zamri</a>, <a href="https://publications.waset.org/search?q=Anis%20Salwa%20Mohd%20Khairuddin"> Anis Salwa Mohd Khairuddin</a>, <a href="https://publications.waset.org/search?q=Norrima%20Mokhtar"> Norrima Mokhtar</a>, <a href="https://publications.waset.org/search?q=Rubiyah%20Yusof"> Rubiyah Yusof</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Effective statistical feature extraction and classification are important in image-based automatic inspection and analysis. An automatic wood species recognition system is designed to perform wood inspection at custom checkpoints to avoid mislabeling of timber which will results to loss of income to the timber industry. The system focuses on analyzing the statistical pores properties of the wood images. This paper proposed a fuzzy-based feature extractor which mimics the experts’ knowledge on wood texture to extract the properties of pores distribution from the wood surface texture. The proposed feature extractor consists of two steps namely pores extraction and fuzzy pores management. The total number of statistical features extracted from each wood image is 38 features. Then, a backpropagation neural network is used to classify the wood species based on the statistical features. A comprehensive set of experiments on a database composed of 5200 macroscopic images from 52 tropical wood species was used to evaluate the performance of the proposed feature extractor. The advantage of the proposed feature extraction technique is that it mimics the experts’ interpretation on wood texture which allows human involvement when analyzing the wood texture. Experimental results show the efficiency of the proposed method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Classification" title="Classification">Classification</a>, <a href="https://publications.waset.org/search?q=fuzzy" title=" fuzzy"> fuzzy</a>, <a href="https://publications.waset.org/search?q=inspection%20system" title=" inspection system"> inspection system</a>, <a href="https://publications.waset.org/search?q=image%20analysis." title=" image analysis."> image analysis.</a> </p> <a href="https://publications.waset.org/10003749/statistical-feature-extraction-method-for-wood-species-recognition-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10003749/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10003749/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10003749/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10003749/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10003749/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10003749/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10003749/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10003749/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10003749/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10003749/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10003749.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1743</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1432</span> 3D CAD Models and its Feature Similarity</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Elmi%20Abu%20Bakar">Elmi Abu Bakar</a>, <a href="https://publications.waset.org/search?q=Tetsuo%20Miyake"> Tetsuo Miyake</a>, <a href="https://publications.waset.org/search?q=Zhong%20Zhang"> Zhong Zhang</a>, <a href="https://publications.waset.org/search?q=Takashi%20Imamura"> Takashi Imamura</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Knowing the geometrical object pose of products in manufacturing line before robot manipulation is required and less time consuming for overall shape measurement. In order to perform it, the information of shape representation and matching of objects is become required. Objects are compared with its descriptor that conceptually subtracted from each other to form scalar metric. When the metric value is smaller, the object is considered closed to each other. Rotating the object from static pose in some direction introduce the change of value in scalar metric value of boundary information after feature extraction of related object. In this paper, a proposal method for indexing technique for retrieval of 3D geometrical models based on similarity between boundaries shapes in order to measure 3D CAD object pose using object shape feature matching for Computer Aided Testing (CAT) system in production line is proposed. In experimental results shows the effectiveness of proposed method.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=CAD" title="CAD">CAD</a>, <a href="https://publications.waset.org/search?q=rendering" title=" rendering"> rendering</a>, <a href="https://publications.waset.org/search?q=feature%20extraction" title=" feature extraction"> feature extraction</a>, <a href="https://publications.waset.org/search?q=feature%20classification." title=" feature classification."> feature classification.</a> </p> <a href="https://publications.waset.org/33/3d-cad-models-and-its-feature-similarity" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/33/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/33/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/33/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/33/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/33/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/33/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/33/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/33/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/33/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/33/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/33.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1979</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1431</span> Voice Command Recognition System Based on MFCC and VQ Algorithms</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Mahdi%20Shaneh">Mahdi Shaneh</a>, <a href="https://publications.waset.org/search?q=Azizollah%20Taheri"> Azizollah Taheri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The goal of this project is to design a system to recognition voice commands. Most of voice recognition systems contain two main modules as follow 鈥渇eature extraction" and 鈥渇eature matching". In this project, MFCC algorithm is used to simulate feature extraction module. Using this algorithm, the cepstral coefficients are calculated on mel frequency scale. VQ (vector quantization) method will be used for reduction of amount of data to decrease computation time. In the feature matching stage Euclidean distance is applied as similarity criterion. Because of high accuracy of used algorithms, the accuracy of this voice command system is high. Using these algorithms, by at least 5 times repetition for each command, in a single training session, and then twice in each testing session zero error rate in recognition of commands is achieved. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=MFCC" title="MFCC">MFCC</a>, <a href="https://publications.waset.org/search?q=Vector%20quantization" title=" Vector quantization"> Vector quantization</a>, <a href="https://publications.waset.org/search?q=Vocal%20tract" title=" Vocal tract"> Vocal tract</a>, <a href="https://publications.waset.org/search?q=Voicecommand." title=" Voicecommand."> Voicecommand.</a> </p> <a href="https://publications.waset.org/4967/voice-command-recognition-system-based-on-mfcc-and-vq-algorithms" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/4967/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/4967/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/4967/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/4967/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/4967/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/4967/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/4967/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/4967/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/4967/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/4967/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/4967.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">3157</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1430</span> Rotation Invariant Face Recognition Based on Hybrid LPT/DCT Features</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Rehab%20F.%20Abdel-Kader">Rehab F. Abdel-Kader</a>, <a href="https://publications.waset.org/search?q=Rabab%20M.%20Ramadan"> Rabab M. Ramadan</a>, <a href="https://publications.waset.org/search?q=Rawya%20Y.%20Rizk"> Rawya Y. Rizk</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The recognition of human faces, especially those with different orientations is a challenging and important problem in image analysis and classification. This paper proposes an effective scheme for rotation invariant face recognition using Log-Polar Transform and Discrete Cosine Transform combined features. The rotation invariant feature extraction for a given face image involves applying the logpolar transform to eliminate the rotation effect and to produce a row shifted log-polar image. The discrete cosine transform is then applied to eliminate the row shift effect and to generate the low-dimensional feature vector. A PSO-based feature selection algorithm is utilized to search the feature vector space for the optimal feature subset. Evolution is driven by a fitness function defined in terms of maximizing the between-class separation (scatter index). Experimental results, based on the ORL face database using testing data sets for images with different orientations; show that the proposed system outperforms other face recognition methods. The overall recognition rate for the rotated test images being 97%, demonstrating that the extracted feature vector is an effective rotation invariant feature set with minimal set of selected features. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Discrete%20Cosine%20Transform" title="Discrete Cosine Transform">Discrete Cosine Transform</a>, <a href="https://publications.waset.org/search?q=Face%20Recognition" title=" Face Recognition"> Face Recognition</a>, <a href="https://publications.waset.org/search?q=Feature%20Extraction" title="Feature Extraction">Feature Extraction</a>, <a href="https://publications.waset.org/search?q=Log%20Polar%20Transform" title=" Log Polar Transform"> Log Polar Transform</a>, <a href="https://publications.waset.org/search?q=Particle%20SwarmOptimization." title=" Particle SwarmOptimization."> Particle SwarmOptimization.</a> </p> <a href="https://publications.waset.org/11753/rotation-invariant-face-recognition-based-on-hybrid-lptdct-features" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/11753/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/11753/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/11753/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/11753/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/11753/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/11753/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/11753/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/11753/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/11753/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/11753/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/11753.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1873</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1429</span> Fast Facial Feature Extraction and Matching with Artificial Face Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Y.%20H.%20Tsai">Y. H. Tsai</a>, <a href="https://publications.waset.org/search?q=Y.%20W.%20Chen"> Y. W. Chen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Facial features are frequently used to represent local properties of a human face image in computer vision applications. In this paper, we present a fast algorithm that can extract the facial features online such that they can give a satisfying representation of a face image. It includes one step for a coarse detection of each facial feature by AdaBoost and another one to increase the accuracy of the found points by Active Shape Models (ASM) in the regions of interest. The resulted facial features are evaluated by matching with artificial face models in the applications of physiognomy. The distance measure between the features and those in the fate models from the database is carried out by means of the Hausdorff distance. In the experiment, the proposed method shows the efficient performance in facial feature extractions and online system of physiognomy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Facial%20feature%20extraction" title="Facial feature extraction">Facial feature extraction</a>, <a href="https://publications.waset.org/search?q=AdaBoost" title=" AdaBoost"> AdaBoost</a>, <a href="https://publications.waset.org/search?q=Active%20shapemodel" title=" Active shapemodel"> Active shapemodel</a>, <a href="https://publications.waset.org/search?q=Hausdorff%20distance" title=" Hausdorff distance"> Hausdorff distance</a> </p> <a href="https://publications.waset.org/5776/fast-facial-feature-extraction-and-matching-with-artificial-face-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/5776/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/5776/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/5776/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/5776/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/5776/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/5776/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/5776/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/5776/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/5776/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/5776/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/5776.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1812</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1428</span> Extraction of Significant Phrases from Text</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Yuan%20J.%20Lui">Yuan J. Lui</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Prospective readers can quickly determine whether a document is relevant to their information need if the significant phrases (or keyphrases) in this document are provided. Although keyphrases are useful, not many documents have keyphrases assigned to them, and manually assigning keyphrases to existing documents is costly. Therefore, there is a need for automatic keyphrase extraction. This paper introduces a new domain independent keyphrase extraction algorithm. The algorithm approaches the problem of keyphrase extraction as a classification task, and uses a combination of statistical and computational linguistics techniques, a new set of attributes, and a new machine learning method to distinguish keyphrases from non-keyphrases. The experiments indicate that this algorithm performs better than other keyphrase extraction tools and that it significantly outperforms Microsoft Word 2000-s AutoSummarize feature. The domain independence of this algorithm has also been confirmed in our experiments.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=classification" title="classification">classification</a>, <a href="https://publications.waset.org/search?q=keyphrase%20extraction" title=" keyphrase extraction"> keyphrase extraction</a>, <a href="https://publications.waset.org/search?q=machine%0D%0Alearning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/search?q=summarization" title=" summarization"> summarization</a> </p> <a href="https://publications.waset.org/9360/extraction-of-significant-phrases-from-text" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/9360/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/9360/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/9360/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/9360/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/9360/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/9360/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/9360/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/9360/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/9360/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/9360/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/9360.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">2051</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1427</span> The Utility of Wavelet Transform in Surface Electromyography Feature Extraction -A Comparative Study of Different Mother Wavelets</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Farzaneh%20Akhavan%20Mahdavi">Farzaneh Akhavan Mahdavi</a>, <a href="https://publications.waset.org/search?q=Siti%20Anom%20Ahmad"> Siti Anom Ahmad</a>, <a href="https://publications.waset.org/search?q=Mohd%20Hamiruce%20Marhaban"> Mohd Hamiruce Marhaban</a>, <a href="https://publications.waset.org/search?q=Mohammad-R.%20Akbarzadeh-T"> Mohammad-R. Akbarzadeh-T</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Electromyography (EMG) signal processing has been investigated remarkably regarding various applications such as in rehabilitation systems. Specifically, wavelet transform has served as a powerful technique to scrutinize EMG signals since wavelet transform is consistent with the nature of EMG as a non-stationary signal. In this paper, the efficiency of wavelet transform in surface EMG feature extraction is investigated from four levels of wavelet decomposition and a comparative study between different mother wavelets had been done. To recognize the best function and level of wavelet analysis, two evaluation criteria, scatter plot and RES index are recruited. Hereupon, four wavelet families, namely, Daubechies, Coiflets, Symlets and Biorthogonal are studied in wavelet decomposition stage. Consequently, the results show that only features from first and second level of wavelet decomposition yields good performance and some functions of various wavelet families can lead to an improvement in separability class of different hand movements.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Electromyography%20signal" title="Electromyography signal">Electromyography signal</a>, <a href="https://publications.waset.org/search?q=feature%20extraction" title=" feature extraction"> feature extraction</a>, <a href="https://publications.waset.org/search?q=wavelettransform" title=" wavelettransform"> wavelettransform</a>, <a href="https://publications.waset.org/search?q=means%20absolute%20value." title=" means absolute value."> means absolute value.</a> </p> <a href="https://publications.waset.org/2502/the-utility-of-wavelet-transform-in-surface-electromyography-feature-extraction-a-comparative-study-of-different-mother-wavelets" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/2502/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/2502/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/2502/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/2502/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/2502/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/2502/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/2502/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/2502/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/2502/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/2502/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/2502.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">2840</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1426</span> Statistics over Lyapunov Exponents for Feature Extraction: Electroencephalographic Changes Detection Case</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Elif%20Derya%20UBEYLI">Elif Derya UBEYLI</a>, <a href="https://publications.waset.org/search?q=Inan%20GULER"> Inan GULER</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>A new approach based on the consideration that electroencephalogram (EEG) signals are chaotic signals was presented for automated diagnosis of electroencephalographic changes. This consideration was tested successfully using the nonlinear dynamics tools, like the computation of Lyapunov exponents. This paper presented the usage of statistics over the set of the Lyapunov exponents in order to reduce the dimensionality of the extracted feature vectors. Since classification is more accurate when the pattern is simplified through representation by important features, feature extraction and selection play an important role in classifying systems such as neural networks. Multilayer perceptron neural network (MLPNN) architectures were formulated and used as basis for detection of electroencephalographic changes. Three types of EEG signals (EEG signals recorded from healthy volunteers with eyes open, epilepsy patients in the epileptogenic zone during a seizure-free interval, and epilepsy patients during epileptic seizures) were classified. The selected Lyapunov exponents of the EEG signals were used as inputs of the MLPNN trained with Levenberg- Marquardt algorithm. The classification results confirmed that the proposed MLPNN has potential in detecting the electroencephalographic changes.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Chaotic%20signal" title="Chaotic signal">Chaotic signal</a>, <a href="https://publications.waset.org/search?q=Electroencephalogram%20%28EEG%29%20signals" title=" Electroencephalogram (EEG) signals"> Electroencephalogram (EEG) signals</a>, <a href="https://publications.waset.org/search?q=Feature%20extraction%2Fselection" title=" Feature extraction/selection"> Feature extraction/selection</a>, <a href="https://publications.waset.org/search?q=Lyapunov%20exponents" title=" Lyapunov exponents"> Lyapunov exponents</a> </p> <a href="https://publications.waset.org/6430/statistics-over-lyapunov-exponents-for-feature-extraction-electroencephalographic-changes-detection-case" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/6430/apa" 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