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基于ICA多特征融合的人脸识别
引用本文:周昌军,魏小鹏,张强,白春光.基于ICA多特征融合的人脸识别[J].应用基础与工程科学学报,2009,17(5):799-809.
作者姓名:周昌军  魏小鹏  张强  白春光
作者单位:1. 大连大学辽宁省智能信息处理重点实验室,辽宁,大连,116622
2. 大连理工大学管理学院,辽宁,大连,116024
基金项目:Foundation item:The National Natural Science Foundation of China,The Program for New Century Excellent Talents in University,The Program for Liaoning Excellent Talents in University,The Program for study of Science of the Educational Department of Liaoning Province ,The Program for study of Science of the Educational Department of Liaoning Province,The Program for Dalian Science and Technology,The open fund of Liaoning Key Lab of Intelligent Information Processing
摘    要:提出了一种基于特征融合的人脸识别方法.该方法首先对预处理后的人脸图像进行全局特征及局部分量的提取,分别采用离散余弦交换(DCT)提取包含图像大量信息的低频部分特征和奇异值分解(SVD)抽取图像的代数特征作为图像的全局特征,采用非负矩阵分解(NMF)提取图像的局部分量特征,然后将此两类特征以独立成份分析(ICA)进行融合,获取用于人脸识别的特征向量.在本文的实验中,我们将此特征向量应用于支持向量机(SVM)进行分类训练及识别测试,并获得较好的结果.

关 键 词:离散余弦变换  奇异值分解  非负矩阵分解  独立成份分析  融合  人脸识别文献标识吗

Face Recognition Based on ICA and Features Fusion
ZHOU Chanjun,WEI Xiaopeng,ZHANG Qiang,BAI Chunguang.Face Recognition Based on ICA and Features Fusion[J].Journal of Basic Science and Engineering,2009,17(5):799-809.
Authors:ZHOU Chanjun  WEI Xiaopeng  ZHANG Qiang  BAI Chunguang
Abstract:We proposod a novel algorithm for facial recognition based on features fusion in support vector machine (SVM). First, some local features and global features from pre-processed face images were obtained. The global features were obtained by making use of discrete cosine transform (DCT) and singular value decomposition (SVD). At the same time, the local features by utilizing non-negative matrix factorization (NMF) were also obtained. Furthermore, the feature vectors fused by independent component analysis (ICA)with global and local features were given. Finally, the feature vectors were used to train SVM to realize the face recognition, and the computer simulation illustrated the effectivity of this method on the ORL face database.
Keywords:A  DCT  SVD  NMF  ICA  fusion  face recognition
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