基于差异性稀疏表示的人脸识别算法

计算机科学 ›› 2014, Vol. 41 ›› Issue (Z6): 178-180.

基于差异性稀疏表示的人脸识别算法

胡伟,张少华,郭晓丽

上海大学自动化系上海200072;南通大学南通226019;上海大学自动化系上海200072;南通大学南通226019

出版日期:2018-11-14 发布日期:2018-11-14
基金资助:
本文受国家自然科学基金项目(61171077),江苏省高校自然科学研究项目(12KJB510025)资助

Discriminative Sparse Representations in Face Recognition

HU Wei,ZHANG Shao-hua and GUO Xiao-li

Online:2018-11-14 Published:2018-11-14

摘要/Abstract

摘要： 针对光照变换产生的阴影、反光等原因,提出了一种差异性稀疏表示的人脸识别算法。首先利用非下采样contourlet变换(NSCT,nonsubsampled contourlet transformation)将测试图像分解。利用不同子带系数特点,依据子带对图像分类的贡献度分类,并将子带信息进行融合,得到具有差异性的特征,最后用于人脸识别。在人脸数据库上的实验结果表明,该算法对于光照和表情变换具有较好的鲁棒性。

关键词: 人脸识别,稀疏表示,差异性,非下采样contourlet变换(NSCT) 中图法分类号TN216文献标识码A

Abstract: In order to alleviate the influence of illumination variations on face recognition,in this paper,we proposed an effective discriminative sparse representation face recognition method．Firstly,we decomposed test image by using nonsubsampled contourlet transformation (NSCT),then used coefficients of each subbands to calculate the contribution of each subbands and fusion the subbands information according to the contribution of each classified image block．Finally,we obtained the discriminative character of the test image,applied it in the face recognition．The experiment on AR database shows that the proposed algorithm is more robust in illumination and expression variations in face recognition．

Key words: Face recognition,Sparse representation,Discriminative,Nonsubsampled contourlet transformation

胡伟,张少华,郭晓丽. 基于差异性稀疏表示的人脸识别算法[J]. 计算机科学, 2014, 41(Z6): 178-180. https://doi.org/

HU Wei,ZHANG Shao-hua and GUO Xiao-li. Discriminative Sparse Representations in Face Recognition[J]. Computer Science, 2014, 41(Z6): 178-180. https://doi.org/

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