Search results for: Ruzelita Ngadiran

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Ngadiran</title> <meta name="description" content="Search results for: Ruzelita Ngadiran"> <meta name="keywords" content="Ruzelita Ngadiran"> <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="Ruzelita Ngadiran"> <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> 1</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: Ruzelita Ngadiran</h1> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1</span> Local Spectrum Feature Extraction for Face Recognition</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Muhammad%20Imran%20Ahmad">Muhammad Imran Ahmad</a>, <a href="https://publications.waset.org/search?q=Ruzelita%20Ngadiran"> Ruzelita Ngadiran</a>, <a href="https://publications.waset.org/search?q=Mohd%20Nazrin%20Md%20Isa"> Mohd Nazrin Md Isa</a>, <a href="https://publications.waset.org/search?q=Nor%20Ashidi%20Mat%20Isa"> Nor Ashidi Mat Isa</a>, <a href="https://publications.waset.org/search?q=Mohd%20Zaizu%20Ilyas"> Mohd Zaizu Ilyas</a>, <a href="https://publications.waset.org/search?q=Raja%20Abdullah%20Raja%20Ahmad"> Raja Abdullah Raja Ahmad</a>, <a href="https://publications.waset.org/search?q=Said%20Amirul%20Anwar%20Ab%20Hamid"> Said Amirul Anwar Ab Hamid</a>, <a href="https://publications.waset.org/search?q=Muzammil%20Jusoh"> Muzammil Jusoh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>This paper presents two techniques, local feature extraction using image spectrum and low frequency spectrum modelling using GMM to capture the underlying statistical information to improve the performance of face recognition system. Local spectrum features are extracted using overlap sub block window that are mapped on the face image. For each of this block, spatial domain is transformed to frequency domain using DFT. A low frequency coefficient is preserved by discarding high frequency coefficients by applying rectangular mask on the spectrum of the facial image. Low frequency information is non- Gaussian in the feature space and by using combination of several Gaussian functions that has different statistical properties, the best feature representation can be modelled using probability density function. The recognition process is performed using maximum likelihood value computed using pre-calculated GMM components. The method is tested using FERET datasets and is able to achieved 92% recognition rates.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Local%20features%20modelling" title="Local features modelling">Local features modelling</a>, <a href="https://publications.waset.org/search?q=face%20recognition%20system" title=" face recognition system"> face recognition system</a>, <a href="https://publications.waset.org/search?q=Gaussian%20mixture%20models." title=" Gaussian mixture models."> Gaussian mixture models.</a> </p> <a href="https://publications.waset.org/10000915/local-spectrum-feature-extraction-for-face-recognition" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10000915/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10000915/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a 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Search results for: Ruzelita Ngadiran