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Comparative Analysis of Partial Occlusion Using Face Recognition Techniques
Nallammal.N, V.Radha
Pages - 132 - 139     |    Revised - 05-04-2013     |    Published - 30-04-2013
Volume - 7   Issue - 2    |    Publication Date - April 2013  Table of Contents
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KEYWORDS
Partial Face Occlusion, Non-negative Matrix Factorization (NMF), Local NMF, Spatially Confined NMF.
ABSTRACT
This paper presents a comparison of partial occlusion using face recognition techniques that gives in which technique produce better result for total success rate. The partial occlusion of face recognition is especially useful for people where part of their face is scarred and defect thus need to be covered. Hence, either top part/eye region or bottom part of face will be recognized respectively. The partial face information are tested with Principle Component Analysis (PCA), Non-negative matrix factorization (NMF), Local NMF (LNMF) and Spatially Confined NMF (SFNMF). The comparative results show that the recognition rate of 95.17% with r = 80 by using SFNMF for bottom face region. On the other hand, eye region achieves 95.12% with r = 10 by using LNMF.
CITED BY (1)  
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Mr. Nallammal.N
Avinashilingam Institute for Hmoe science and Higher Education for Women - India
msg2nalls@gmail.com
Dr. V.Radha
Associate Professor /Dept of computer Science Avinashilingam Institute for home science and Higher education for Women Coimbatore, 641 043, Tamil nadu,India - India