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基于图像矩阵变换的PCA及人脸自动识别
引用本文:刘永俊,谈云飞,朱晓宇,常晋义.基于图像矩阵变换的PCA及人脸自动识别[J].常熟理工学院学报,2009,23(2):101-105.
作者姓名:刘永俊  谈云飞  朱晓宇  常晋义
作者单位:常熟理工学院,计算机学院软件工程系,江苏,常熟,215500
基金项目:常熟理工学院青年基金 
摘    要:在图像主分量分析的基础上,提出了一种基于图像矩阵变换的主分量分析方法.该方法首先对图像矩阵进行适当的变换,用得到的新的图像矩阵构造图像总体散布矩阵后,再运用图像投影主分量分析进行特征抽取.该方法在ORL标准人脸库上的试验结果表明,经过适当的变换后抽取的鉴别特征在识别性能和速率上均优于单纯的图像主分量分析方法.另外,在AR人脸库上的试验结果也表明该方法对光照变化具有较强的鲁棒性.

关 键 词:图像矩阵变换  图像主分量分析  主分量分析  特征抽取  人脸识别

Principal Component Analysis(PCA) Based on Changing Image Matrices and Face Recognition
LIU Yong-jun,TAN Yun-fei,ZHU Xiao-yu,CHANG Jin-yi.Principal Component Analysis(PCA) Based on Changing Image Matrices and Face Recognition[J].Journal of Changshu Institute of Technology,2009,23(2):101-105.
Authors:LIU Yong-jun  TAN Yun-fei  ZHU Xiao-yu  CHANG Jin-yi
Institution:Department of Software Engineering;Changshu Insitute of Technology;Changshu 215500;China
Abstract:A new image feature extraction method based on changing image matrices and image principal component analysis(CIMPCA) is proposed in this paper.It has an applicable change of the primitive image matrices,so that the dimension of the image total scatter matrix is further minified.Then,image principal component analysis(IMPCA)is used to do image feature extraction.Finally,the experimental results testing on ORL database indicate that the proposed method is more effective than just using IMPCA simply.Its consu...
Keywords:changing image matrices  image principal component analysis (IMPCA)  principal component analysis (PCA)  image feature extraction  face recognition
本文献已被 CNKI 维普 万方数据 等数据库收录!
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