吉林大学学报(理学版)

• 计算机 • 上一篇    下一篇

基于改进的2DPCA对近红外人脸图像的识别方法

吴博, 刘小华, 周春光   

  1. 吉林大学 计算机科学与技术学院, 长春 130012
  • 收稿日期:2013-03-14 出版日期:2014-03-26 发布日期:2014-03-20
  • 通讯作者: 吴博 E-mail:wubo_aaa@163.com

Near Infrared Human Face Image Recognition Based onthe Improved TwoDimensional Principal Component Analysis

WU Bo, LIU Xiaohua, ZHOU Chunguang   

  1. College of Computer Science and Technology, Jilin University, Changchun 130012, China
  • Received:2013-03-14 Online:2014-03-26 Published:2014-03-20
  • Contact: WU Bo E-mail:wubo_aaa@163.com

摘要:

基于二维主成分分析(twodimensional principal component analysis, 2DPCA)算法与近红外人脸识别方法, 提出一种双向2DPCA算法和双向对称2DPCA
算法, 得到了识别率更高的人脸识别方法, 解决了环境光照对人脸识别的影响.

关键词: 人脸识别, 近红外, 2DPCA算法, 双向2DPCA算法, 双向对称2DPCA算法

Abstract:

The authors used twodimensional principal component analysis algorithm and the near infrared face method to solve the influence of environmental light on the face recognition, on the basis of which the authors advanced the twoway twodimensional principal component analysis algorithm and twoway symmetric twodimensional principal component analysis algorithm, and got the higher recognition rate of face recognition methods.

Key words: face recognition, near infrared, twodimensional principal component analysis algorithm, twoway twodimensional principal component analysis algorithm, twoway symmetrical twodimensional principal component analysis algorithm

中图分类号: 

  • TP391.4