›› 2014, Vol. 27 ›› Issue (1): 45-.

• 论文 • 上一篇    下一篇



  1. (西安电子科技大学 理学院,陕西 西安 710071)
  • 出版日期:2014-01-15 发布日期:2014-01-12
  • 作者简介:穆新亮(1988—),男,硕士研究生。研究方向:模式识别,支持向量机,最优化计算方法。E-mail:muxinliang168@163.com。武亚静(1988—),女,硕士研究生。研究方向:模式识别,支持向量机,最优化计算方法。

Face Recognition Algorithm Based on Bidirectional Principal Component Analysis and Compressed Sensing

 MU Xin-Liang, WU Ya-Jing   

  1. (School of Science,Xidian University,Xi'an 710071,China)
  • Online:2014-01-15 Published:2014-01-12



关键词: 双向主成分分析(BD-PCA), 压缩感知, 人脸识别


This paper proposes a face recognition algorithm combining the bidirectional principal component analysis (BD-PCA) and the face recognition algorithm based on smooth l0 norm(SL0).First we use BD-PCA to reduce the dimension of these training images,and then make each face image into a vector by stretching it according to each column,and use these vectors to comprise a dictionary matrix,and process test images in the same way,and finally solve the optimization problem by SL0 algorithm.Experimental results show that the proposed algorithm achieves high recognition rate and better reconstruction effect than those by BD-PCA and SL0 algorithm alone.

Key words: BD-PCA;CS;face recognition


  • TP391.41