文章基本信息

标题：Performance Comparison of Face Recognition Algorithms based on face image Retrieval
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作者：Mokhtari Hicham ; Idir Belaidi ; Alem Said 等
期刊名称：Research Journal of Recent Sciences
电子版ISSN：2277-2502
出版年度：2013
卷号：2
期号：12
页码：65-73
语种：English
出版社：International Science Community Association
摘要：Biometric systems are complex systems of safety measures based on physical, biological and the humans behavioral. The automatic face recognition has become a highly active research area, mainly due to numbers published papers in recent years. In this paper, we present a comparative study for evaluation of face recognition system based on face restoration. Our study is performed in two consecutive steps, In the first step, we use two methods of image restoration called Centralized sparse representation (CSR) and adaptive sparse domain selection with adaptive regularization (ASDS-AR) while in the second step the set of methods that have been used are principal component analysis (PCA), linear discriminant analysis (LDA) kernel principal component analysis (KPCA) and Kernel Fisher Analysis (KFA) for face recognition and we associated the Gabor Wavelets and Phase Congruency in order to achieve the evaluation of our proposed model. In addition, the comparative analysis on the ORL database is also employed in the experiments to evaluate the susceptibility of the appearance based methods on various image degradations which can occur in real-life operating conditions. Our experimental results suggest that Gabor linear discriminant analysis (GLDA) ensures the most consistent verification rates across the tested ORL databases for both methods CSR and ASDS-AR.
关键词：Face recognition;centralized sparse representation;adaptive sparse domain selection and adaptive regularization;image deblurring;ORL databases