计算机工程 ›› 2008, Vol. 34 ›› Issue (14): 179-181.doi: 10.3969/j.issn.1000-3428.2008.14.064

• 人工智能及识别技术 • 上一篇    下一篇

基于粗糙集和mPCA的人脸识别算法

任小康1,李文静1,靳艳峰2   

  1. (1. 西北师范大学数学与信息科学学院,兰州 730070;2. 兰州理工大学计算机与通信学院,兰州 730070)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2008-07-20 发布日期:2008-07-20

Face Recognition Algorithm Based on Rough Set and mPCA

REN Xiao-kang1, LI Wen-jing1, JIN Yan-feng2   

  1. (1. College of Mathematics and Information Science, Northwest Normal University, Lanzhou 730070;2. College of Computer and Communication, Lanzhou University of Technology, Lanzhou 730070)
  • Received:1900-01-01 Revised:1900-01-01 Online:2008-07-20 Published:2008-07-20

摘要: 提出了一种粗糙集与mPCA相结合的人脸识别算法。根据一定规则将人脸图像模块化,对每一个小模块利用PCA进行处理,对于经过PCA降维后的数据再利用粗糙集约减,去除冗余信息。该方法可以减少姿势表情的变化给人脸识别带来的影响,去除大量的冗余信息,从而降低计算的复杂性,提高识别率。基于ORL人脸数据库的实验结果表明,该算法正确识别率达到97%。

关键词: 粗糙集, 属性约减, 人脸识别

Abstract: This paper proposes a new face recognition approach based on rough set and mPCA. It modularizes the face images according to some very rules; and deals with the modular images by using PCA, reduces the data which has been descented by PCA. This method not only reduces the influence to face recognition brought by the change of pose and expression of the face images, but also wipes off a lot of redundant data. Thereby, it reduces the complexity of computation and enhances the recognition rate observably. Experimental result based on ORL face database shows that the correct recognition ratio can reach 97 percent.

Key words: rough set, attributes reduction, face recognition

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