文章基本信息

标题：Sparse Representation Approach for Variation-Robust Face Recognition Using Discrete Wavelet Transform
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作者：Rania Salah El-Sayed ; Mohamedyoussri El-Nahas ; Ahmed El Kholy 等
期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2012
卷号：9
期号：6
出版社：IJCSI Press
摘要：Face recognition has become one of the most challenging tasks in the pattern recognition field and it is very important for many applications such as: video surveillance, forensic applications criminal investigations, and in many other fields it is also very useful. In this paper we are using sparse representation approach based on discrete wavelet transform (DWT) to achieve more robustness to variation in lighting, directions and expressions, because sparse representation does not exterminate obstacles posed by several practical issues, such as lighting, pose, and especially facial expressions, which tend to distort almost all the features and can thus compromise the accuracy of sparse representation. The result of new proposed approach is compared with sparse representation approach to show that the proposed approach is more robust to illumination, direction and expression variations than sparse representation.
关键词：Face recognition; L1;minimization; sparse representation; discrete wavelet transform (DWT).