基于改进的2DPCA对近红外人脸图像的识别方法  

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

作　　者：吴博[1] 刘小华[1] 周春光[1] 

机构地区：[1]吉林大学计算机科学与技术学院,长春130012

出　　处：《吉林大学学报（理学版）》2014年第2期303-307,共5页Journal of Jilin University:Science Edition

基　　金：国家自然科学基金(批准号:61175023)

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.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.

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 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]