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Ukasha</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Data security needed in data transmission, storage, and communication to ensure the security. The color image is decomposed into red, green, and blue channels. The blue and green channels are compressed using 3-levels discrete wavelet transform. The Arnold transform uses to changes the locations of red image channel pixels as image scrambling process. Then all these channels are encrypted separately using a key image that has same original size and is generating using private keys and modulo operations. Performing the X-OR and modulo operations between the encrypted channels images for image pixel values change purpose. The extracted contours of color image recovery can be obtained with accepted level of distortion using Canny edge detector. Experiments have demonstrated that proposed algorithm can fully encrypt 2D color image and completely reconstructed without any distortion. It has shown that the color image can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=color%20image" title="color image">color image</a>, <a href="https://publications.waset.org/abstracts/search?q=wavelet%20transform" title=" wavelet transform"> wavelet transform</a>, <a href="https://publications.waset.org/abstracts/search?q=edge%20detector" title=" edge detector"> edge detector</a>, <a href="https://publications.waset.org/abstracts/search?q=Arnold%20transform" title=" Arnold transform"> Arnold transform</a>, <a href="https://publications.waset.org/abstracts/search?q=lossy%20image%20encryption" title=" lossy image encryption"> lossy image encryption</a> </p> <a href="https://publications.waset.org/abstracts/16468/an-efficient-encryption-scheme-using-dwt-and-arnold-transforms" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16468.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">489</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1609</span> Bitplanes Gray-Level Image Encryption Approach Using Arnold Transform</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ali%20Abdrhman%20M.%20Ukasha">Ali Abdrhman M. Ukasha</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Data security needed in data transmission, storage, and communication to ensure the security. The single step parallel contour extraction (SSPCE) method is used to create the edge map as a key image from the different Gray level/Binary image. Performing the X-OR operation between the key image and each bit plane of the original image for image pixel values change purpose. The Arnold transform used to changes the locations of image pixels as image scrambling process. Experiments have demonstrated that proposed algorithm can fully encrypt 2D Gary level image and completely reconstructed without any distortion. Also shown that the analyzed algorithm have extremely large security against some attacks like salt & pepper and JPEG compression. Its proof that the Gray level image can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=SSPCE%20method" title="SSPCE method">SSPCE method</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20compression-salt-%20peppers%20attacks" title=" image compression-salt- peppers attacks"> image compression-salt- peppers attacks</a>, <a href="https://publications.waset.org/abstracts/search?q=bitplanes%20decomposition" title=" bitplanes decomposition"> bitplanes decomposition</a>, <a href="https://publications.waset.org/abstracts/search?q=Arnold%20transform" title=" Arnold transform"> Arnold transform</a>, <a href="https://publications.waset.org/abstracts/search?q=lossless%20image%20encryption" title=" lossless image encryption"> lossless image encryption</a> </p> <a href="https://publications.waset.org/abstracts/14573/bitplanes-gray-level-image-encryption-approach-using-arnold-transform" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14573.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">442</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1608</span> Bitplanes Image Encryption/Decryption Using Edge Map (SSPCE Method) and Arnold Transform</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ali%20A.%20Ukasha">Ali A. Ukasha</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Data security needed in data transmission, storage, and communication to ensure the security. The single step parallel contour extraction (SSPCE) method is used to create the edge map as a key image from the different Gray level/Binary image. Performing the X-OR operation between the key image and each bit plane of the original image for image pixel values change purpose. The Arnold transform used to changes the locations of image pixels as image scrambling process. Experiments have demonstrated that proposed algorithm can fully encrypt 2D Gary level image and completely reconstructed without any distortion. Also shown that the analyzed algorithm have extremely large security against some attacks like salt & pepper and JPEG compression. Its proof that the Gray level image can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=SSPCE%20method" title="SSPCE method">SSPCE method</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20compression" title=" image compression"> image compression</a>, <a href="https://publications.waset.org/abstracts/search?q=salt%20and%0D%0Apeppers%20attacks" title=" salt and peppers attacks"> salt and peppers attacks</a>, <a href="https://publications.waset.org/abstracts/search?q=bitplanes%20decomposition" title=" bitplanes decomposition"> bitplanes decomposition</a>, <a href="https://publications.waset.org/abstracts/search?q=Arnold%20transform" title=" Arnold transform"> Arnold transform</a>, <a href="https://publications.waset.org/abstracts/search?q=lossless%20image%20encryption" title=" lossless image encryption"> lossless image encryption</a> </p> <a href="https://publications.waset.org/abstracts/14570/bitplanes-image-encryptiondecryption-using-edge-map-sspce-method-and-arnold-transform" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14570.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">503</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1607</span> Voice Liveness Detection Using Kolmogorov Arnold Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Arth%20J.%20Shah">Arth J. Shah</a>, <a href="https://publications.waset.org/abstracts/search?q=Madhu%20R.%20Kamble"> Madhu R. Kamble</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Voice biometric liveness detection is customized to certify an authentication process of the voice data presented is genuine and not a recording or synthetic voice. With the rise of deepfakes and other equivalently sophisticated spoofing generation techniques, it鈥檚 becoming challenging to ensure that the person on the other end is a live speaker or not. Voice Liveness Detection (VLD) system is a group of security measures which detect and prevent voice spoofing attacks. Motivated by the recent development of the Kolmogorov-Arnold Network (KAN) based on the Kolmogorov-Arnold theorem, we proposed KAN for the VLD task. To date, multilayer perceptron (MLP) based classifiers have been used for the classification tasks. We aim to capture not only the compositional structure of the model but also to optimize the values of univariate functions. This study explains the mathematical as well as experimental analysis of KAN for VLD tasks, thereby opening a new perspective for scientists to work on speech and signal processing-based tasks. This study emerges as a combination of traditional signal processing tasks and new deep learning models, which further proved to be a better combination for VLD tasks. The experiments are performed on the POCO and ASVSpoof 2017 V2 database. We used Constant Q-transform, Mel, and short-time Fourier transform (STFT) based front-end features and used CNN, BiLSTM, and KAN as back-end classifiers. The best accuracy is 91.26 % on the POCO database using STFT features with the KAN classifier. In the ASVSpoof 2017 V2 database, the lowest EER we obtained was 26.42 %, using CQT features and KAN as a classifier. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kolmogorov%20Arnold%20networks" title="Kolmogorov Arnold networks">Kolmogorov Arnold networks</a>, <a href="https://publications.waset.org/abstracts/search?q=multilayer%20perceptron" title=" multilayer perceptron"> multilayer perceptron</a>, <a href="https://publications.waset.org/abstracts/search?q=pop%20noise" title=" pop noise"> pop noise</a>, <a href="https://publications.waset.org/abstracts/search?q=voice%20liveness%20detection" title=" voice liveness detection"> voice liveness detection</a> </p> <a href="https://publications.waset.org/abstracts/187492/voice-liveness-detection-using-kolmogorov-arnold-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/187492.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">48</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1606</span> Color Image Compression/Encryption/Contour Extraction using 3L-DWT and SSPCE Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ali%20A.%20Ukasha">Ali A. Ukasha</a>, <a href="https://publications.waset.org/abstracts/search?q=Majdi%20F.%20Elbireki"> Majdi F. Elbireki</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20F.%20Abdullah"> Mohammad F. Abdullah</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Data security needed in data transmission, storage, and communication to ensure the security. This paper is divided into two parts. This work interests with the color image which is decomposed into red, green and blue channels. The blue and green channels are compressed using 3-levels discrete wavelet transform. The Arnold transform uses to changes the locations of red image channel pixels as image scrambling process. Then all these channels are encrypted separately using the key image that has same original size and are generating using private keys and modulo operations. Performing the X-OR and modulo operations between the encrypted channels images for image pixel values change purpose. The extracted contours from color images recovery can be obtained with accepted level of distortion using single step parallel contour extraction (SSPCE) method. Experiments have demonstrated that proposed algorithm can fully encrypt 2D Color images and completely reconstructed without any distortion. Also shown that the analyzed algorithm has extremely large security against some attacks like salt and pepper and Jpeg compression. Its proof that the color images can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=SSPCE%20method" title="SSPCE method">SSPCE method</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20compression%20and%20salt%20and%20peppers%20attacks" title=" image compression and salt and peppers attacks"> image compression and salt and peppers attacks</a>, <a href="https://publications.waset.org/abstracts/search?q=bitplanes%20decomposition" title=" bitplanes decomposition"> bitplanes decomposition</a>, <a href="https://publications.waset.org/abstracts/search?q=Arnold%20transform" title=" Arnold transform"> Arnold transform</a>, <a href="https://publications.waset.org/abstracts/search?q=color%20image" title=" color image"> color image</a>, <a href="https://publications.waset.org/abstracts/search?q=wavelet%20transform" title=" wavelet transform"> wavelet transform</a>, <a href="https://publications.waset.org/abstracts/search?q=lossless%20image%20encryption" title=" lossless image encryption"> lossless image encryption</a> </p> <a href="https://publications.waset.org/abstracts/18519/color-image-compressionencryptioncontour-extraction-using-3l-dwt-and-sspce-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18519.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">525</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1605</span> Robust Data Image Watermarking for Data Security</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Harsh%20Vikram%20Singh">Harsh Vikram Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Ankur%20Rai"> Ankur Rai</a>, <a href="https://publications.waset.org/abstracts/search?q=Anand%20Mohan"> Anand Mohan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we propose secure and robust data hiding algorithm based on DCT by Arnold transform and chaotic sequence. The watermark image is scrambled by Arnold cat map to increases its security and then the chaotic map is used for watermark signal spread in middle band of DCT coefficients of the cover image The chaotic map can be used as pseudo-random generator for digital data hiding, to increase security and robustness .Performance evaluation for robustness and imperceptibility of proposed algorithm has been made using bit error rate (BER), normalized correlation (NC), and peak signal to noise ratio (PSNR) value for different watermark and cover images such as Lena, Girl, Tank images and gain factor .We use a binary logo image and text image as watermark. The experimental results demonstrate that the proposed algorithm achieves higher security and robustness against JPEG compression as well as other attacks such as addition of noise, low pass filtering and cropping attacks compared to other existing algorithm using DCT coefficients. Moreover, to recover watermarks in proposed algorithm, there is no need to original cover image. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=data%20hiding" title="data hiding">data hiding</a>, <a href="https://publications.waset.org/abstracts/search?q=watermarking" title=" watermarking"> watermarking</a>, <a href="https://publications.waset.org/abstracts/search?q=DCT" title=" DCT"> DCT</a>, <a href="https://publications.waset.org/abstracts/search?q=chaotic%20sequence" title=" chaotic sequence"> chaotic sequence</a>, <a href="https://publications.waset.org/abstracts/search?q=arnold%20transforms" title=" arnold transforms"> arnold transforms</a> </p> <a href="https://publications.waset.org/abstracts/29055/robust-data-image-watermarking-for-data-security" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/29055.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">520</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1604</span> The Desire to Know: Arnold鈥檚 Contribution to a Psychological Conceptualization of Academic Motivation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=F.%20Ruiz-Fuster">F. Ruiz-Fuster</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Arnold’s redefinition of human motives can sustain a psychology of education which emphasizes the beauty of knowledge and the exercise of intellectual functions. Thus, education instead of focusing on skills and learning by doing would be centered on ‘the widest reaches of the human spirit’. One way to attain it is by developing children’s inherent interest. Arnold takes into account the fact that the desire to know is the inherent interest which leads students to explore and learn. She also emphasizes the need of exercising human functions as thinking, judging and reasoning. According to Arnold, the influence of psychological theories of motivation in education has derived in considering that all learning and school tasks should derive from children’s needs and impulses. The desire to know and the curiosity have not been considered as basic and active as any instinctive drive or basic need, so there has been an attempt to justify and understand how biological drives guide student’s learning. However, understanding motives and motivation not as a drive, an instinct or an impulse guided by our basic needs, but as a want that leads to action can help to understand, from a psychological perspective, how teachers can motivate students to learn, strengthening their desire and interest to reason and discover the whole new world of knowledge. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=academic%20motivation" title="academic motivation">academic motivation</a>, <a href="https://publications.waset.org/abstracts/search?q=interests" title=" interests"> interests</a>, <a href="https://publications.waset.org/abstracts/search?q=desire%20to%20know" title=" desire to know"> desire to know</a>, <a href="https://publications.waset.org/abstracts/search?q=educational%20psychology" title=" educational psychology"> educational psychology</a>, <a href="https://publications.waset.org/abstracts/search?q=intellectual%20functions" title=" intellectual functions"> intellectual functions</a> </p> <a href="https://publications.waset.org/abstracts/102345/the-desire-to-know-arnolds-contribution-to-a-psychological-conceptualization-of-academic-motivation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/102345.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">156</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1603</span> Multilevel Gray Scale Image Encryption through 2D Cellular Automata</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rupali%20Bhardwaj">Rupali Bhardwaj</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Cryptography is the science of using mathematics to encrypt and decrypt data; the data are converted into some other gibberish form, and then the encrypted data are transmitted. The primary purpose of this paper is to provide two levels of security through a two-step process, rather than transmitted the message bits directly, first encrypted it using 2D cellular automata and then scrambled with Arnold Cat Map transformation; it provides an additional layer of protection and reduces the chance of the transmitted message being detected. A comparative analysis on effectiveness of scrambling technique is provided by scrambling degree measurement parameters i.e. Gray Difference Degree (GDD) and Correlation Coefficient. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=scrambling" title="scrambling">scrambling</a>, <a href="https://publications.waset.org/abstracts/search?q=cellular%20automata" title=" cellular automata"> cellular automata</a>, <a href="https://publications.waset.org/abstracts/search?q=Arnold%20cat%20map" title=" Arnold cat map"> Arnold cat map</a>, <a href="https://publications.waset.org/abstracts/search?q=game%20of%20life" title=" game of life"> game of life</a>, <a href="https://publications.waset.org/abstracts/search?q=gray%20difference%20degree" title=" gray difference degree"> gray difference degree</a>, <a href="https://publications.waset.org/abstracts/search?q=correlation%20coefficient" title=" correlation coefficient"> correlation coefficient</a> </p> <a href="https://publications.waset.org/abstracts/41177/multilevel-gray-scale-image-encryption-through-2d-cellular-automata" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41177.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">382</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1602</span> Video Compression Using Contourlet Transform</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Delara%20Kazempour">Delara Kazempour</a>, <a href="https://publications.waset.org/abstracts/search?q=Mashallah%20Abasi%20Dezfuli"> Mashallah Abasi Dezfuli</a>, <a href="https://publications.waset.org/abstracts/search?q=Reza%20Javidan"> Reza Javidan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Video compression used for channels with limited bandwidth and storage devices has limited storage capabilities. One of the most popular approaches in video compression is the usage of different transforms. Discrete cosine transform is one of the video compression methods that have some problems such as blocking, noising and high distortion inappropriate effect in compression ratio. wavelet transform is another approach is better than cosine transforms in balancing of compression and quality but the recognizing of curve curvature is so limit. Because of the importance of the compression and problems of the cosine and wavelet transforms, the contourlet transform is most popular in video compression. In the new proposed method, we used contourlet transform in video image compression. Contourlet transform can save details of the image better than the previous transforms because this transform is multi-scale and oriented. This transform can recognize discontinuity such as edges. In this approach we lost data less than previous approaches. Contourlet transform finds discrete space structure. This transform is useful for represented of two dimension smooth images. This transform, produces compressed images with high compression ratio along with texture and edge preservation. Finally, the results show that the majority of the images, the parameters of the mean square error and maximum signal-to-noise ratio of the new method based contourlet transform compared to wavelet transform are improved but in most of the images, the parameters of the mean square error and maximum signal-to-noise ratio in the cosine transform is better than the method based on contourlet transform. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=video%20compression" title="video compression">video compression</a>, <a href="https://publications.waset.org/abstracts/search?q=contourlet%20transform" title=" contourlet transform"> contourlet transform</a>, <a href="https://publications.waset.org/abstracts/search?q=discrete%20cosine%20transform" title=" discrete cosine transform"> discrete cosine transform</a>, <a href="https://publications.waset.org/abstracts/search?q=wavelet%20transform" title=" wavelet transform"> wavelet transform</a> </p> <a href="https://publications.waset.org/abstracts/6930/video-compression-using-contourlet-transform" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/6930.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">452</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1601</span> A Robust Hybrid Blind Digital Image Watermarking System Using Discrete Wavelet Transform and Contourlet Transform </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nidal%20F.%20Shilbayeh">Nidal F. Shilbayeh</a>, <a href="https://publications.waset.org/abstracts/search?q=Belal%20AbuHaija"> Belal AbuHaija</a>, <a href="https://publications.waset.org/abstracts/search?q=Zainab%20N.%20Al-Qudsy"> Zainab N. Al-Qudsy</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, a hybrid blind digital watermarking system using Discrete Wavelet Transform (DWT) and Contourlet Transform (CT) has been implemented and tested. The implemented combined digital watermarking system has been tested against five common types of image attacks. The performance evaluation shows improved results in terms of imperceptibility, robustness, and high tolerance against these attacks; accordingly, the system is very effective and applicable. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=discrete%20wavelet%20transform%20%28DWT%29" title="discrete wavelet transform (DWT)">discrete wavelet transform (DWT)</a>, <a href="https://publications.waset.org/abstracts/search?q=contourlet%20transform%20%28CT%29" title=" contourlet transform (CT)"> contourlet transform (CT)</a>, <a href="https://publications.waset.org/abstracts/search?q=digital%20image%20watermarking" title=" digital image watermarking"> digital image watermarking</a>, <a href="https://publications.waset.org/abstracts/search?q=copyright%20protection" title=" copyright protection"> copyright protection</a>, <a href="https://publications.waset.org/abstracts/search?q=geometric%20attack" title=" geometric attack"> geometric attack</a> </p> <a href="https://publications.waset.org/abstracts/69379/a-robust-hybrid-blind-digital-image-watermarking-system-using-discrete-wavelet-transform-and-contourlet-transform" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/69379.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">400</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1600</span> Donoho-Stark鈥檚 and Hardy鈥檚 Uncertainty Principles for the Short-Time Quaternion Offset Linear Canonical Transform</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Younus%20Bhat">Mohammad Younus Bhat</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The quaternion offset linear canonical transform (QOLCT), which isa time-shifted and frequency-modulated version of the quaternion linear canonical transform (QLCT), provides a more general framework of most existing signal processing tools. For the generalized QOLCT, the classical Heisenberg鈥檚 and Lieb鈥檚 uncertainty principles have been studied recently. In this paper, we first define the short-time quaternion offset linear canonical transform (ST-QOLCT) and drive its relationship with the quaternion Fourier transform (QFT). The crux of the paper lies in the generalization of several well-known uncertainty principles for the ST-QOLCT, including Donoho-Stark鈥檚 uncertainty principle, Hardy鈥檚 uncertainty principle, Beurling鈥檚 uncertainty principle, and the logarithmic uncertainty principle. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Quaternion%20Fourier%20transform" title="Quaternion Fourier transform">Quaternion Fourier transform</a>, <a href="https://publications.waset.org/abstracts/search?q=Quaternion%20offset%20linear%20canonical%20transform" title=" Quaternion offset linear canonical transform"> Quaternion offset linear canonical transform</a>, <a href="https://publications.waset.org/abstracts/search?q=short-time%20quaternion%20offset%20linear%20canonical%20transform" title=" short-time quaternion offset linear canonical transform"> short-time quaternion offset linear canonical transform</a>, <a href="https://publications.waset.org/abstracts/search?q=uncertainty%20principle" title=" uncertainty principle"> uncertainty principle</a> </p> <a href="https://publications.waset.org/abstracts/142375/donoho-starks-and-hardys-uncertainty-principles-for-the-short-time-quaternion-offset-linear-canonical-transform" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/142375.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">219</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1599</span> Fingerprint Image Encryption Using a 2D Chaotic Map and Elliptic Curve Cryptography</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=D.%20M.%20S.%20Bandara">D. M. S. Bandara</a>, <a href="https://publications.waset.org/abstracts/search?q=Yunqi%20Lei"> Yunqi Lei</a>, <a href="https://publications.waset.org/abstracts/search?q=Ye%20Luo"> Ye Luo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Fingerprints are suitable as long-term markers of human identity since they provide detailed and unique individual features which are difficult to alter and durable over life time. In this paper, we propose an algorithm to encrypt and decrypt fingerprint images by using a specially designed Elliptic Curve Cryptography (ECC) procedure based on block ciphers. In addition, to increase the confusing effect of fingerprint encryption, we also utilize a chaotic-behaved method called Arnold Cat Map (ACM) for a 2D scrambling of pixel locations in our method. Experimental results are carried out with various types of efficiency and security analyses. As a result, we demonstrate that the proposed fingerprint encryption/decryption algorithm is advantageous in several different aspects including efficiency, security and flexibility. In particular, using this algorithm, we achieve a margin of about 0.1% in the test of Number of Pixel Changing Rate (NPCR) values comparing to the-state-of-the-art performances. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=arnold%20cat%20map" title="arnold cat map">arnold cat map</a>, <a href="https://publications.waset.org/abstracts/search?q=biometric%20encryption" title=" biometric encryption"> biometric encryption</a>, <a href="https://publications.waset.org/abstracts/search?q=block%20cipher" title=" block cipher"> block cipher</a>, <a href="https://publications.waset.org/abstracts/search?q=elliptic%20curve%20cryptography" title=" elliptic curve cryptography"> elliptic curve cryptography</a>, <a href="https://publications.waset.org/abstracts/search?q=fingerprint%20encryption" title=" fingerprint encryption"> fingerprint encryption</a>, <a href="https://publications.waset.org/abstracts/search?q=Koblitz%E2%80%99s%20%20encoding" title=" Koblitz鈥檚 encoding"> Koblitz鈥檚 encoding</a> </p> <a href="https://publications.waset.org/abstracts/96251/fingerprint-image-encryption-using-a-2d-chaotic-map-and-elliptic-curve-cryptography" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/96251.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">209</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1598</span> The Optical OFDM Equalization Based on the Fractional Fourier Transform</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20Cherifi">A. Cherifi</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20S.%20Bouazza"> B. S. Bouazza</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20O.%20Dahman"> A. O. Dahman</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20Yagoubi"> B. Yagoubi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Transmission over Optical channels will introduce inter-symbol interference (ISI) as well as inter-channel (or inter-carrier) interference (ICI). To decrease the effects of ICI, this paper proposes equalizer for the Optical OFDM system based on the fractional Fourier transform (FrFFT). In this FrFT-OFDM system, traditional Fourier transform is replaced by fractional Fourier transform to modulate and demodulate the data symbols. The equalizer proposed consists of sampling the received signal in the different time per time symbol. Theoretical analysis and numerical simulation are discussed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=OFDM" title="OFDM">OFDM</a>, <a href="https://publications.waset.org/abstracts/search?q=fractional%20fourier%20transform" title=" fractional fourier transform"> fractional fourier transform</a>, <a href="https://publications.waset.org/abstracts/search?q=internet%20and%20information%20technology" title=" internet and information technology"> internet and information technology</a> </p> <a href="https://publications.waset.org/abstracts/27211/the-optical-ofdm-equalization-based-on-the-fractional-fourier-transform" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/27211.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">411</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1597</span> Yu Kwang-Chung vs. Yu Kwang-Chung: Untranslatability as the Touchstone of a Poet</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Min-Hua%20Wu">Min-Hua Wu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The untranslatability of an established poet鈥檚 tour de force is thoroughly explored by Matthew Arnold (1822-1888). In his On Translating Homer (1861), Arnold lists the four most striking poetic qualities of Homer, namely his rapidity, plainness and directness of style and diction, plainness and directness of ideas, and nobleness. He concludes that such celebrated English translators as Cowper, Pope, Chapman, and Mr. Newman are all doomed, due to their respective failure in rendering the totality of the four Homeric poetic qualities. Why poetic translation always amounts to being proven such a mission impossible for the translator? According to Arnold, it is because there constantly exists a mist interposed between the translator鈥檚 own literary self-obsession and the objective artistic qualities that reside in the work of the original author. Foregrounding such a seemingly empowering yet actually detrimental poetic mist, he explains why the aforementioned translators fail in their attempts to bring the Homeric charm to the British reader. Drawing on Arnold鈥檚 analytical study on Homeric translation, the research attempts to bring Yu Kwang-chung the poet vis-脿-vis Yu Kwang-chung the translator, with an aim not so much to find any similar mist as revealed by Arnold between his Chinese poetry and English translation as to probe into a latent and veiled literary and lingual mist interposed between Chinese and English, if not between Chinese and English literatures. The major work studied and analyzed for this study is Yu鈥檚 own Chinese poetry and his own English translation collected in The Night Watchman: Yu Kwang-chung 1958-2004. The research argues that the following critical elements that characterizes Yu鈥檚 poetics are to a certain extent 'transformed,' if not 'lost,' in his English translation: a. the Chinese pictographic and ideographic unit terms which so unfailingly characterize the poet鈥檚 incredible creativity, allowing him to habitually and conveniently coin concrete textual images or word-scapes almost at his own will; b. the subtle wordplay and punning which appear at a reasonable frequency; c. the parallel contrastive repetitive syntactic structure within a single poetic line; d. the ambiguous and highly associative diction in the adjective and noun categories; e. the literary allusion that harks back to the old times of Chinese literature; f. the alliteration that adds rhythm and smoothness to the lines; g. the rhyming patterns that bring about impressive sonority and lingering echo to the ears of the reader; h. the grandeur-imposing and sublimity-arousing word-scaping which hinges on the employment of verbs; i. the meandering cultural heritage that embraces such elements as Chinese medicine and kung fu; and j. other features of the like. Once we appeal to the Arnoldian tribunal and resort to the strict standards of such a Victorian cultural and literary critic who insists 'to see the object as in itself it really is,' we may serve as a potential judge for the tug of war between Yu Kwang-chung the poet and Yu Kwang-chung the translator, a tug of war that will not merely broaden our understating of Chinese poetics but deepen our apprehension of Chinese-English translatology. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yu%20Kwang-chung" title="Yu Kwang-chung">Yu Kwang-chung</a>, <a href="https://publications.waset.org/abstracts/search?q=The%20Night%20Watchman" title=" The Night Watchman"> The Night Watchman</a>, <a href="https://publications.waset.org/abstracts/search?q=poetry%20translation" title=" poetry translation"> poetry translation</a>, <a href="https://publications.waset.org/abstracts/search?q=Chinese-English%20translation" title=" Chinese-English translation"> Chinese-English translation</a>, <a href="https://publications.waset.org/abstracts/search?q=translation%20studies" title=" translation studies"> translation studies</a>, <a href="https://publications.waset.org/abstracts/search?q=Matthew%20Arnold" title=" Matthew Arnold"> Matthew Arnold</a> </p> <a href="https://publications.waset.org/abstracts/84232/yu-kwang-chung-vs-yu-kwang-chung-untranslatability-as-the-touchstone-of-a-poet" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/84232.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">398</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1596</span> Restriction Theorem for the Fourier-Dunkl Transform and its Applications</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=P.%20Jitendra%20Kumar%20Senapati">P. Jitendra Kumar Senapati</a>, <a href="https://publications.waset.org/abstracts/search?q=Pradeep%20B."> Pradeep B.</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20S.%20Mondal"> S. S. Mondal</a>, <a href="https://publications.waset.org/abstracts/search?q=H.%20Mejjaoli"> H. Mejjaoli</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Fourier-Dunkl transform, which generalizes the Fourier transform, is defined, and Strichartz鈥檚 restriction theorem for the Fourier-Dunkl transform on any general surfaces given by quadratic polynomials is studied. In particular, surfaces such as the cone, paraboloid, sphere, and hyperboloid are considered. Furthermore, the generalization of the restriction theorem for the Fourier-Dunkl transform is investigated, extending it from functional inequalities involving a single function to systems of orthonormal functions. To establish restriction theorems for the Fourier-Dunkl transform for the above surfaces, the Fourier-Dunkl transform of certain generalized functions is computed. A general theory is developed, and a sufficient condition is provided to prove the restriction theorems and their generalization to systems of orthonormal functions. As an application of the restriction theorem, Strichartz estimates for orthonormal families of initial data associated with the Schrodinger 篓 propagator, wave propagator, and Klein-Gordon propagator under the Dunkl Laplacian are derived. This restriction theorem generalizes the Stein-Tomas and Strichartz restriction theorems in specific cases. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=dunkl%20laplacian" title="dunkl laplacian">dunkl laplacian</a>, <a href="https://publications.waset.org/abstracts/search?q=fourier-dunkl%20transform" title=" fourier-dunkl transform"> fourier-dunkl transform</a>, <a href="https://publications.waset.org/abstracts/search?q=klein-gordon%20equation" title=" klein-gordon equation"> klein-gordon equation</a>, <a href="https://publications.waset.org/abstracts/search?q=orthonormal%20strichartz%20inequalities" title=" orthonormal strichartz inequalities"> orthonormal strichartz inequalities</a>, <a href="https://publications.waset.org/abstracts/search?q=restriction%20theorem" title=" restriction theorem"> restriction theorem</a> </p> <a href="https://publications.waset.org/abstracts/198791/restriction-theorem-for-the-fourier-dunkl-transform-and-its-applications" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/198791.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">2</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1595</span> Equalization Algorithm for the Optical OFDM System Based on the Fractional Fourier Transform </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20Cherifi">A. Cherifi</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20Bouazza"> B. Bouazza</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20O.%20Dahmane"> A. O. Dahmane</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20Yagoubi"> B. Yagoubi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Transmission over Optical channels will introduce inter-symbol interference (ISI) as well as inter-channel (or inter-carrier) interference (ICI). To decrease the effects of ICI, this paper proposes equalizer for the Optical OFDM system based on the fractional Fourier transform (FrFFT). In this FrFT-OFDM system, traditional Fourier transform is replaced by fractional Fourier transform to modulate and demodulate the data symbols. The equalizer proposed consists of sampling the received signal in the different time per time symbol. Theoretical analysis and numerical simulation are discussed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=OFDM" title="OFDM">OFDM</a>, <a href="https://publications.waset.org/abstracts/search?q=%28FrFT%29%20fractional%20fourier%20transform" title=" (FrFT) fractional fourier transform"> (FrFT) fractional fourier transform</a>, <a href="https://publications.waset.org/abstracts/search?q=optical%20OFDM" title=" optical OFDM"> optical OFDM</a>, <a href="https://publications.waset.org/abstracts/search?q=equalization%20algorithm" title=" equalization algorithm"> equalization algorithm</a> </p> <a href="https://publications.waset.org/abstracts/23848/equalization-algorithm-for-the-optical-ofdm-system-based-on-the-fractional-fourier-transform" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/23848.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">432</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1594</span> Applying Wavelet Transform to Ferroresonance Detection and Protection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chun-Wei%20Huang">Chun-Wei Huang</a>, <a href="https://publications.waset.org/abstracts/search?q=Jyh-Cherng%20Gu"> Jyh-Cherng Gu</a>, <a href="https://publications.waset.org/abstracts/search?q=Ming-Ta%20Yang"> Ming-Ta Yang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Non-synchronous breakage or line failure in power systems with light or no loads can lead to core saturation in transformers or potential transformers. This can cause component and capacitance matching resulting in the formation of resonant circuits, which trigger ferroresonance. This study employed a wavelet transform for the detection of ferroresonance. Simulation results demonstrate the efficacy of the proposed method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ferroresonance" title="ferroresonance">ferroresonance</a>, <a href="https://publications.waset.org/abstracts/search?q=wavelet%20transform" title=" wavelet transform"> wavelet transform</a>, <a href="https://publications.waset.org/abstracts/search?q=intelligent%20electronic%20device" title=" intelligent electronic device"> intelligent electronic device</a>, <a href="https://publications.waset.org/abstracts/search?q=transformer" title=" transformer"> transformer</a> </p> <a href="https://publications.waset.org/abstracts/12919/applying-wavelet-transform-to-ferroresonance-detection-and-protection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/12919.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">502</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1593</span> Hit-Or-Miss Transform as a Tool for Similar Shape Detection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Osama%20Mohamed%20Elrajubi">Osama Mohamed Elrajubi</a>, <a href="https://publications.waset.org/abstracts/search?q=Idris%20El-Feghi"> Idris El-Feghi</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Abu%20Baker%20Saghayer"> Mohamed Abu Baker Saghayer</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper describes an identification of specific shapes within binary images using the morphological Hit-or-Miss Transform (HMT). Hit-or-Miss transform is a general binary morphological operation that can be used in searching of particular patterns of foreground and background pixels in an image. It is actually a basic operation of binary morphology since almost all other binary morphological operators are derived from it. The input of this method is a binary image and a structuring element (a template which will be searched in a binary image) while the output is another binary image. In this paper a modification of Hit-or-Miss transform has been proposed. The accuracy of algorithm is adjusted according to the similarity of the template and the sought template. The implementation of this method has been done by C language. The algorithm has been tested on several images and the results have shown that this new method can be used for similar shape detection. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hit-or-miss%20operator%20transform" title="hit-or-miss operator transform">hit-or-miss operator transform</a>, <a href="https://publications.waset.org/abstracts/search?q=HMT" title=" HMT"> HMT</a>, <a href="https://publications.waset.org/abstracts/search?q=binary%20morphological%20operation" title=" binary morphological operation"> binary morphological operation</a>, <a href="https://publications.waset.org/abstracts/search?q=shape%20detection" title=" shape detection"> shape detection</a>, <a href="https://publications.waset.org/abstracts/search?q=binary%20images%20processing" title=" binary images processing"> binary images processing</a> </p> <a href="https://publications.waset.org/abstracts/11881/hit-or-miss-transform-as-a-tool-for-similar-shape-detection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/11881.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">339</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1592</span> Content Based Face Sketch Images Retrieval in WHT, DCT, and DWT Transform Domain</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=W.%20S.%20Besbas">W. S. Besbas</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20A.%20Artemi"> M. A. Artemi</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20M.%20Salman"> R. M. Salman</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Content based face sketch retrieval can be used to find images of criminals from their sketches for 'Crime Prevention'. This paper investigates the problem of CBIR of face sketch images in transform domain. Face sketch images that are similar to the query image are retrieved from the face sketch database. Features of the face sketch image are extracted in the spectrum domain of a selected transforms. These transforms are Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), and Walsh Hadamard Transform (WHT). For the performance analyses of features selection methods three face images databases are used. These are 'Sheffield face database', 'Olivetti Research Laboratory (ORL) face database', and 'Indian face database'. The City block distance measure is used to evaluate the performance of the retrieval process. The investigation concludes that, the retrieval rate is database dependent. But in general, the DCT is the best. On the other hand, the WHT is the best with respect to the speed of retrieving images. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Content%20Based%20Image%20Retrieval%20%28CBIR%29" title="Content Based Image Retrieval (CBIR)">Content Based Image Retrieval (CBIR)</a>, <a href="https://publications.waset.org/abstracts/search?q=face%20sketch%20image%20retrieval" title=" face sketch image retrieval"> face sketch image retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=features%20selection%20for%20CBIR" title=" features selection for CBIR"> features selection for CBIR</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20retrieval%20in%20transform%20domain" title=" image retrieval in transform domain"> image retrieval in transform domain</a> </p> <a href="https://publications.waset.org/abstracts/8251/content-based-face-sketch-images-retrieval-in-wht-dct-and-dwt-transform-domain" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/8251.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">499</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1591</span> Reduced Differential Transform Methods for Solving the Fractional Diffusion Equations</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yildiray%20Keskin">Yildiray Keskin</a>, <a href="https://publications.waset.org/abstracts/search?q=Omer%20Acan"> Omer Acan</a>, <a href="https://publications.waset.org/abstracts/search?q=Murat%20Akkus"> Murat Akkus</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, the solution of fractional diffusion equations is presented by means of the reduced differential transform method. Fractional partial differential equations have special importance in engineering and sciences. Application of reduced differential transform method to this problem shows the rapid convergence of the sequence constructed by this method to the exact solution. The numerical results show that the approach is easy to implement and accurate when applied to fractional diffusion equations. The method introduces a promising tool for solving many fractional partial differential equations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fractional%20diffusion%20equations" title="fractional diffusion equations">fractional diffusion equations</a>, <a href="https://publications.waset.org/abstracts/search?q=Caputo%20fractional%20derivative" title=" Caputo fractional derivative"> Caputo fractional derivative</a>, <a href="https://publications.waset.org/abstracts/search?q=reduced%20differential%20transform%20method" title=" reduced differential transform method"> reduced differential transform method</a>, <a href="https://publications.waset.org/abstracts/search?q=partial" title=" partial"> partial</a> </p> <a href="https://publications.waset.org/abstracts/17526/reduced-differential-transform-methods-for-solving-the-fractional-diffusion-equations" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17526.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">534</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1590</span> An Image Enhancement Method Based on Curvelet Transform for CBCT-Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shahriar%20Farzam">Shahriar Farzam</a>, <a href="https://publications.waset.org/abstracts/search?q=Maryam%20Rastgarpour"> Maryam Rastgarpour</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Image denoising plays extremely important role in digital image processing. Enhancement of clinical image research based on Curvelet has been developed rapidly in recent years. In this paper, we present a method for image contrast enhancement for cone beam CT (CBCT) images based on fast discrete curvelet transforms (FDCT) that work through Unequally Spaced Fast Fourier Transform (USFFT). These transforms return a table of Curvelet transform coefficients indexed by a scale parameter, an orientation and a spatial location. Accordingly, the coefficients obtained from FDCT-USFFT can be modified in order to enhance contrast in an image. Our proposed method first uses a two-dimensional mathematical transform, namely the FDCT through unequal-space fast Fourier transform on input image and then applies thresholding on coefficients of Curvelet to enhance the CBCT images. Consequently, applying unequal-space fast Fourier Transform leads to an accurate reconstruction of the image with high resolution. The experimental results indicate the performance of the proposed method is superior to the existing ones in terms of Peak Signal to Noise Ratio (PSNR) and Effective Measure of Enhancement (EME). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=curvelet%20transform" title="curvelet transform">curvelet transform</a>, <a href="https://publications.waset.org/abstracts/search?q=CBCT" title=" CBCT"> CBCT</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20enhancement" title=" image enhancement"> image enhancement</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20denoising" title=" image denoising"> image denoising</a> </p> <a href="https://publications.waset.org/abstracts/69244/an-image-enhancement-method-based-on-curvelet-transform-for-cbct-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/69244.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">304</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1589</span> Application of the Discrete Rationalized Haar Transform to Distributed Parameter System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Joon-Hoon%20Park">Joon-Hoon Park</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper the rationalized Haar transform is applied for distributed parameter system identification and estimation. A distributed parameter system is a dynamical and mathematical model described by a partial differential equation. And system identification concerns the problem of determining mathematical models from observed data. The Haar function has some disadvantages of calculation because it contains irrational numbers, for these reasons the rationalized Haar function that has only rational numbers. The algorithm adopted in this paper is based on the transform and operational matrix of the rationalized Haar function. This approach provides more convenient and efficient computational results. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=distributed%20parameter%20system" title="distributed parameter system">distributed parameter system</a>, <a href="https://publications.waset.org/abstracts/search?q=rationalized%20Haar%20transform" title=" rationalized Haar transform"> rationalized Haar transform</a>, <a href="https://publications.waset.org/abstracts/search?q=operational%20matrix" title=" operational matrix"> operational matrix</a>, <a href="https://publications.waset.org/abstracts/search?q=system%20identification" title=" system identification "> system identification </a> </p> <a href="https://publications.waset.org/abstracts/24246/application-of-the-discrete-rationalized-haar-transform-to-distributed-parameter-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/24246.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">513</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1588</span> Meteosat Second Generation Image Compression Based on the Radon Transform and Linear Predictive Coding: Comparison and Performance </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Cherifi%20Mehdi">Cherifi Mehdi</a>, <a href="https://publications.waset.org/abstracts/search?q=Lahdir%20Mourad"> Lahdir Mourad</a>, <a href="https://publications.waset.org/abstracts/search?q=Ameur%20Soltane"> Ameur Soltane</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Image compression is used to reduce the number of bits required to represent an image. The Meteosat Second Generation satellite (MSG) allows the acquisition of 12 image files every 15 minutes. Which results a large databases sizes. The transform selected in the images compression should contribute to reduce the data representing the images. The Radon transform retrieves the Radon points that represent the sum of the pixels in a given angle for each direction. Linear predictive coding (LPC) with filtering provides a good decorrelation of Radon points using a Predictor constitute by the Symmetric Nearest Neighbor filter (SNN) coefficients, which result losses during decompression. Finally, Run Length Coding (RLC) gives us a high and fixed compression ratio regardless of the input image. In this paper, a novel image compression method based on the Radon transform and linear predictive coding (LPC) for MSG images is proposed. MSG image compression based on the Radon transform and the LPC provides a good compromise between compression and quality of reconstruction. A comparison of our method with other whose two based on DCT and one on DWT bi-orthogonal filtering is evaluated to show the power of the Radon transform in its resistibility against the quantization noise and to evaluate the performance of our method. Evaluation criteria like PSNR and the compression ratio allows showing the efficiency of our method of compression. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=image%20compression" title="image compression">image compression</a>, <a href="https://publications.waset.org/abstracts/search?q=radon%20transform" title=" radon transform"> radon transform</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20predictive%20coding%20%28LPC%29" title=" linear predictive coding (LPC)"> linear predictive coding (LPC)</a>, <a href="https://publications.waset.org/abstracts/search?q=run%20lengthcoding%20%28RLC%29" title=" run lengthcoding (RLC)"> run lengthcoding (RLC)</a>, <a href="https://publications.waset.org/abstracts/search?q=meteosat%20second%20generation%20%28MSG%29" title=" meteosat second generation (MSG)"> meteosat second generation (MSG)</a> </p> <a href="https://publications.waset.org/abstracts/16434/meteosat-second-generation-image-compression-based-on-the-radon-transform-and-linear-predictive-coding-comparison-and-performance" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16434.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">427</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1587</span> A Two-Dimensional Problem Micropolar Thermoelastic Medium under the Effect of Laser Irradiation and Distributed Sources</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Devinder%20Singh">Devinder Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Rajneesh%20Kumar"> Rajneesh Kumar</a>, <a href="https://publications.waset.org/abstracts/search?q=Arvind%20Kumar"> Arvind Kumar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The present investigation deals with the deformation of micropolar generalized thermoelastic solid subjected to thermo-mechanical loading due to a thermal laser pulse. Laplace transform and Fourier transform techniques are used to solve the problem. Thermo-mechanical laser interactions are taken as distributed sources to describe the application of the approach. The closed form expressions of normal stress, tangential stress, coupled stress and temperature are obtained in the domain. Numerical inversion technique of Laplace transform and Fourier transform has been implied to obtain the resulting quantities in the physical domain after developing a computer program. The normal stress, tangential stress, coupled stress and temperature are depicted graphically to show the effect of relaxation times. Some particular cases of interest are deduced from the present investigation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=pulse%20laser" title="pulse laser">pulse laser</a>, <a href="https://publications.waset.org/abstracts/search?q=integral%20transform" title=" integral transform"> integral transform</a>, <a href="https://publications.waset.org/abstracts/search?q=thermoelastic" title=" thermoelastic"> thermoelastic</a>, <a href="https://publications.waset.org/abstracts/search?q=boundary%20value%20problem" title=" boundary value problem"> boundary value problem</a> </p> <a href="https://publications.waset.org/abstracts/33535/a-two-dimensional-problem-micropolar-thermoelastic-medium-under-the-effect-of-laser-irradiation-and-distributed-sources" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/33535.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">621</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1586</span> A Hybrid Watermarking Scheme Using Discrete and Discrete Stationary Wavelet Transformation For Color Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=B%C3%BClent%20Kantar">B眉lent Kantar</a>, <a href="https://publications.waset.org/abstracts/search?q=Numan%20%C3%9Cnald%C4%B1"> Numan 脺nald谋</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a new method which includes robust and invisible digital watermarking on images that is colored. Colored images are used as watermark. Frequency region is used for digital watermarking. Discrete wavelet transform and discrete stationary wavelet transform are used for frequency region transformation. Low, medium and high frequency coefficients are obtained by applying the two-level discrete wavelet transform to the original image. Low frequency coefficients are obtained by applying one level discrete stationary wavelet transform separately to all frequency coefficient of the two-level discrete wavelet transformation of the original image. For every low frequency coefficient obtained from one level discrete stationary wavelet transformation, watermarks are added. Watermarks are added to all frequency coefficients of two-level discrete wavelet transform. Totally, four watermarks are added to original image. In order to get back the watermark, the original and watermarked images are applied with two-level discrete wavelet transform and one level discrete stationary wavelet transform. The watermark is obtained from difference of the discrete stationary wavelet transform of the low frequency coefficients. A total of four watermarks are obtained from all frequency of two-level discrete wavelet transform. Obtained watermark results are compared with real watermark results, and a similarity result is obtained. A watermark is obtained from the highest similarity values. Proposed methods of watermarking are tested against attacks of the geometric and image processing. The results show that proposed watermarking method is robust and invisible. All features of frequencies of two level discrete wavelet transform watermarking are combined to get back the watermark from the watermarked image. Watermarks have been added to the image by converting the binary image. These operations provide us with better results in getting back the watermark from watermarked image by attacking of the geometric and image processing. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=watermarking" title="watermarking">watermarking</a>, <a href="https://publications.waset.org/abstracts/search?q=DWT" title=" DWT"> DWT</a>, <a href="https://publications.waset.org/abstracts/search?q=DSWT" title=" DSWT"> DSWT</a>, <a href="https://publications.waset.org/abstracts/search?q=copy%20right%20protection" title=" copy right protection"> copy right protection</a>, <a href="https://publications.waset.org/abstracts/search?q=RGB" title=" RGB "> RGB </a> </p> <a href="https://publications.waset.org/abstracts/16927/a-hybrid-watermarking-scheme-using-discrete-and-discrete-stationary-wavelet-transformation-for-color-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16927.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">538</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1585</span> Differential Transform Method: Some Important Examples</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Jamil%20Amir">M. Jamil Amir</a>, <a href="https://publications.waset.org/abstracts/search?q=Rabia%20Iqbal"> Rabia Iqbal</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Yaseen"> M. Yaseen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we solve some differential equations analytically by using differential transform method. For this purpose, we consider four models of Laplace equation with two Dirichlet and two Neumann boundary conditions and K(2,2) equation and obtain the corresponding exact solutions. The obtained results show the simplicity of the method and massive reduction in calculations when one compares it with other iterative methods, available in literature. It is worth mentioning that here only a few number of iterations are required to reach the closed form solutions as series expansions of some known functions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=differential%20transform%20method" title="differential transform method">differential transform method</a>, <a href="https://publications.waset.org/abstracts/search?q=laplace%20equation" title=" laplace equation"> laplace equation</a>, <a href="https://publications.waset.org/abstracts/search?q=Dirichlet%20boundary%20conditions" title=" Dirichlet boundary conditions"> Dirichlet boundary conditions</a>, <a href="https://publications.waset.org/abstracts/search?q=Neumann%20boundary%20conditions" title=" Neumann boundary conditions"> Neumann boundary conditions</a> </p> <a href="https://publications.waset.org/abstracts/18605/differential-transform-method-some-important-examples" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18605.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">546</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1584</span> 2.5D Face Recognition Using Gabor Discrete Cosine Transform</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ali%20Cheraghian">Ali Cheraghian</a>, <a href="https://publications.waset.org/abstracts/search?q=Farshid%20Hajati"> Farshid Hajati</a>, <a href="https://publications.waset.org/abstracts/search?q=Soheila%20Gheisari"> Soheila Gheisari</a>, <a href="https://publications.waset.org/abstracts/search?q=Yongsheng%20Gao"> Yongsheng Gao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we present a novel 2.5D face recognition method based on Gabor Discrete Cosine Transform (GDCT). In the proposed method, the Gabor filter is applied to extract feature vectors from the texture and the depth information. Then, Discrete Cosine Transform (DCT) is used for dimensionality and redundancy reduction to improve computational efficiency. The system is combined texture and depth information in the decision level, which presents higher performance compared to methods, which use texture and depth information, separately. The proposed algorithm is examined on publically available Bosphorus database including models with pose variation. The experimental results show that the proposed method has a higher performance compared to the benchmark. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gabor%20filter" title="Gabor filter">Gabor filter</a>, <a href="https://publications.waset.org/abstracts/search?q=discrete%20cosine%20transform" title=" discrete cosine transform"> discrete cosine transform</a>, <a href="https://publications.waset.org/abstracts/search?q=2.5d%20face%20recognition" title=" 2.5d face recognition"> 2.5d face recognition</a>, <a href="https://publications.waset.org/abstracts/search?q=pose" title=" pose"> pose</a> </p> <a href="https://publications.waset.org/abstracts/37341/25d-face-recognition-using-gabor-discrete-cosine-transform" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/37341.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">333</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1583</span> Development of a Few-View Computed Tomographic Reconstruction Algorithm Using Multi-Directional Total Variation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chia%20Jui%20Hsieh">Chia Jui Hsieh</a>, <a href="https://publications.waset.org/abstracts/search?q=Jyh%20Cheng%20Chen"> Jyh Cheng Chen</a>, <a href="https://publications.waset.org/abstracts/search?q=Chih%20Wei%20Kuo"> Chih Wei Kuo</a>, <a href="https://publications.waset.org/abstracts/search?q=Ruei%20Teng%20Wang"> Ruei Teng Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Woei%20Chyn%20Chu"> Woei Chyn Chu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Compressed sensing (CS) based computed tomographic (CT) reconstruction algorithm utilizes total variation (TV) to transform CT image into sparse domain and minimizes L1-norm of sparse image for reconstruction. Different from the traditional CS based reconstruction which only calculates x-coordinate and y-coordinate TV to transform CT images into sparse domain, we propose a multi-directional TV to transform tomographic image into sparse domain for low-dose reconstruction. Our method considers all possible directions of TV calculations around a pixel, so the sparse transform for CS based reconstruction is more accurate. In 2D CT reconstruction, we use eight-directional TV to transform CT image into sparse domain. Furthermore, we also use 26-directional TV for 3D reconstruction. This multi-directional sparse transform method makes CS based reconstruction algorithm more powerful to reduce noise and increase image quality. To validate and evaluate the performance of this multi-directional sparse transform method, we use both Shepp-Logan phantom and a head phantom as the targets for reconstruction with the corresponding simulated sparse projection data (angular sampling interval is 5 deg and 6 deg, respectively). From the results, the multi-directional TV method can reconstruct images with relatively less artifacts compared with traditional CS based reconstruction algorithm which only calculates x-coordinate and y-coordinate TV. We also choose RMSE, PSNR, UQI to be the parameters for quantitative analysis. From the results of quantitative analysis, no matter which parameter is calculated, the multi-directional TV method, which we proposed, is better. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=compressed%20sensing%20%28CS%29" title="compressed sensing (CS)">compressed sensing (CS)</a>, <a href="https://publications.waset.org/abstracts/search?q=low-dose%20CT%20reconstruction" title=" low-dose CT reconstruction"> low-dose CT reconstruction</a>, <a href="https://publications.waset.org/abstracts/search?q=total%20variation%20%28TV%29" title=" total variation (TV)"> total variation (TV)</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-directional%20gradient%20operator" title=" multi-directional gradient operator"> multi-directional gradient operator</a> </p> <a href="https://publications.waset.org/abstracts/77716/development-of-a-few-view-computed-tomographic-reconstruction-algorithm-using-multi-directional-total-variation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/77716.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">261</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1582</span> A Fast Version of the Generalized Multi-Directional Radon Transform</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ines%20Elouedi">Ines Elouedi</a>, <a href="https://publications.waset.org/abstracts/search?q=Atef%20Hammouda"> Atef Hammouda</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a new fast version of the generalized Multi-Directional Radon Transform method. The new method uses the inverse Fast Fourier Transform to lead to a faster Generalized Radon projections. We prove in this paper that the fast algorithm leads to almost the same results of the eldest one but with a considerable lower time computation cost. The projection end result of the fast method is a parameterized Radon space where a high valued pixel allows the detection of a curve from the original image. The proposed fast inversion algorithm leads to an exact reconstruction of the initial image from the Radon space. We show examples of the impact of this algorithm on the pattern recognition domain. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fast%20generalized%20multi-directional%20Radon%20transform" title="fast generalized multi-directional Radon transform">fast generalized multi-directional Radon transform</a>, <a href="https://publications.waset.org/abstracts/search?q=curve" title=" curve"> curve</a>, <a href="https://publications.waset.org/abstracts/search?q=exact%20reconstruction" title=" exact reconstruction"> exact reconstruction</a>, <a href="https://publications.waset.org/abstracts/search?q=pattern%20recognition" title=" pattern recognition"> pattern recognition</a> </p> <a href="https://publications.waset.org/abstracts/69691/a-fast-version-of-the-generalized-multi-directional-radon-transform" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/69691.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">283</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1581</span> Construction of Graph Signal Modulations via Graph Fourier Transform and Its Applications</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Xianwei%20Zheng">Xianwei Zheng</a>, <a href="https://publications.waset.org/abstracts/search?q=Yuan%20Yan%20Tang"> Yuan Yan Tang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Classical window Fourier transform has been widely used in signal processing, image processing, machine learning and pattern recognition. The related Gabor transform is powerful enough to capture the texture information of any given dataset. Recently, in the emerging field of graph signal processing, researchers devoting themselves to develop a graph signal processing theory to handle the so-called graph signals. Among the new developing theory, windowed graph Fourier transform has been constructed to establish a time-frequency analysis framework of graph signals. The windowed graph Fourier transform is defined by using the translation and modulation operators of graph signals, following the similar calculations in classical windowed Fourier transform. Specifically, the translation and modulation operators of graph signals are defined by using the Laplacian eigenvectors as follows. For a given graph signal, its translation is defined by a similar manner as its definition in classical signal processing. Specifically, the translation operator can be defined by using the Fourier atoms; the graph signal translation is defined similarly by using the Laplacian eigenvectors. The modulation of the graph can also be established by using the Laplacian eigenvectors. The windowed graph Fourier transform based on these two operators has been applied to obtain time-frequency representations of graph signals. Fundamentally, the modulation operator is defined similarly to the classical modulation by multiplying a graph signal with the entries in each Fourier atom. However, a single Laplacian eigenvector entry cannot play a similar role as the Fourier atom. This definition ignored the relationship between the translation and modulation operators. In this paper, a new definition of the modulation operator is proposed and thus another time-frequency framework for graph signal is constructed. Specifically, the relationship between the translation and modulation operations can be established by the Fourier transform. Specifically, for any signal, the Fourier transform of its translation is the modulation of its Fourier transform. Thus, the modulation of any signal can be defined as the inverse Fourier transform of the translation of its Fourier transform. Therefore, similarly, the graph modulation of any graph signal can be defined as the inverse graph Fourier transform of the translation of its graph Fourier. The novel definition of the graph modulation operator established a relationship of the translation and modulation operations. The new modulation operation and the original translation operation are applied to construct a new framework of graph signal time-frequency analysis. Furthermore, a windowed graph Fourier frame theory is developed. Necessary and sufficient conditions for constructing windowed graph Fourier frames, tight frames and dual frames are presented in this paper. The novel graph signal time-frequency analysis framework is applied to signals defined on well-known graphs, e.g. Minnesota road graph and random graphs. Experimental results show that the novel framework captures new features of graph signals. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=graph%20signals" title="graph signals">graph signals</a>, <a href="https://publications.waset.org/abstracts/search?q=windowed%20graph%20Fourier%20transform" title=" windowed graph Fourier transform"> windowed graph Fourier transform</a>, <a href="https://publications.waset.org/abstracts/search?q=windowed%20graph%20Fourier%20frames" title=" windowed graph Fourier frames"> windowed graph Fourier frames</a>, <a href="https://publications.waset.org/abstracts/search?q=vertex%20frequency%20analysis" title=" vertex frequency analysis"> vertex frequency analysis</a> </p> <a href="https://publications.waset.org/abstracts/63133/construction-of-graph-signal-modulations-via-graph-fourier-transform-and-its-applications" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/63133.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">346</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=Arnold%20transform&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=Arnold%20transform&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=Arnold%20transform&page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=Arnold%20transform&page=5">5</a></li> <li class="page-item"><a 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