计算机工程 ›› 2011, Vol. 37 ›› Issue (18): 188-189.doi: 10.3969/j.issn.1000-3428.2011.18.062

• 人工智能及识别技术 • 上一篇    下一篇

基于Haar小波和保局投影的人脸识别

李伟生,宋吴斌,周丽芳   

  1. (重庆邮电大学计算机科学与技术学院,重庆 400065)
  • 收稿日期:2011-03-22 出版日期:2011-09-20 发布日期:2011-09-20
  • 作者简介:李伟生(1975-),男,教授、博士,主研方向:智能信息处理,模式识别;宋吴斌,硕士研究生;周丽芳,讲师
  • 基金项目:

    国家自然科学基金资助项目(60842003);教育部科学技 术研究基金资助重点项目;重庆市教委科学技术研究基金资助项目(KJ100525, KJ100519)

Face Recognition Based on Haar Wavelet and Locality Preserving Projections

LI Wei-Sheng, SONG Wu-bin, ZHOU Li-fang   

  1. (College of Computer Science and Technology, Chongqing University of Posts and Telecommumications, Chongqing 400065, China)
  • Received:2011-03-22 Online:2011-09-20 Published:2011-09-20

摘要: 运用保局投影(LPP)算法进行人脸识别时,噪声会破坏真实流形。为此,提出一种解决噪声的新方法——HaarLPP方法。该方法利用Haar小波变换降低噪声的影响,运用LPP算法进行降维,依据最近邻准则完成人脸识别。基于AT&T与Sheffiled人脸数据库的实验结果表明,该方法在噪声的敏感性方面优于传统LPP算法。

关键词: 人脸识别, 特征提取, Haar小波变换, 保局投影, 最近邻分类

Abstract: For the use of Locality Preserving Projections(LPP) for face recognition and the real flow is damaged by noise, this paper presents a new method, named HaarLPP method, to solve the noise. The method uses Haar wavelet transformation to reduce the effect of noise. Face recognition is completed by the LPP dimensionality reduction and the nearest neighbor criteria. Experimental results based on AT&T and Sheffiled face database show that the method is superior to the traditional LPP algorithm in term of the noise sensibility.

Key words: face recognition, feature extraction, Haar wavelet transformation, Locality Preserving Projections(LPP), nearest neighbor classification

中图分类号: