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改进OMP算法在人脸识别中的应用
引用本文:殷爱菡,姜辉明,张清淼.改进OMP算法在人脸识别中的应用[J].计算机工程,2012,38(12):146-148.
作者姓名:殷爱菡  姜辉明  张清淼
作者单位:华东交通大学信息工程学院,南昌,330013
基金项目:国家自然科学基金资助项目
摘    要:分析稀疏表示的人脸识别方法的基本原理,针对采用基于正交匹配追踪(OMP)的稀疏表示算法时,所获得稀疏系数存在负值的问题,提出一种改进的正交匹配追踪算法。通过对稀疏系数的大小进行直接约束,减少负值稀疏系数的产生及算法迭代次数,并提高人脸识别速度。在ORL人脸数据库中的实验结果证明,改进后算法的识别率比原有算法提高了3%,迭代次数设置为7次最为合理。

关 键 词:人脸识别  正交匹配追踪  稀疏表示  稀疏系数  信号重构  压缩感知
收稿时间:2011-08-30

Application of Improved OMP Algorithm in Face Recognition
YIN Ai-han , JIANG Hui-ming , ZHANG Qing-miao.Application of Improved OMP Algorithm in Face Recognition[J].Computer Engineering,2012,38(12):146-148.
Authors:YIN Ai-han  JIANG Hui-ming  ZHANG Qing-miao
Affiliation:(School of Information Engineering,East China Jiaotong University,Nanchang 330013,China)
Abstract:The fundamental principle of face recognition based on sparse representation is analyzed.When sparse representation algorithm based on Orthogonal Matching Pursuit(OMP) is adopted,the obtained sparse coefficient can be negative.To solve this problem,an improved orthogonal matching pursuit algorithm is presented.By directly limiting the sparse coefficient,the proposed method can reduce the amount of negative sparse coefficient and iterations.Meanwhile,face recognition is speeded up.Experiment on the ORL database show that the recognition rate of improved algorithm is 3% higher than the original one,and the most suitable iteration times is 7.
Keywords:face recognition  Orthogonal Matching Pursuit(OMP)  sparse representation  sparse coefficient  signal reconstruction  compressed sensing
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