基于环形对称Gabor变换和PCA加权的人脸识别算法  

Face Recognition Based on Circularly Symmetrical Gabor Transforms and Weighted PCA

作　　者：王进军[1] 王汇源[1,2] 吴晓娟[1] 

机构地区：[1]山东大学信息科学与工程学院,济南250100 [2]Instituto de Engenharia Electronicae Telemotica de Aveiro, Universidade de Aveiro, Campus Universitario de Santiago, 3810-193 Aveiro, Portugal

出　　处：《模式识别与人工智能》2009年第4期635-638,共4页Pattern Recognition and Artificial Intelligence

基　　金：国家自然科学基金资助项目(No.60675024)

摘　　要：环形对称Gabor变换不但具有Gabor小波的一般特性,而且具有信息冗余度小、严格的旋转不变性等优点.文中提出一种基于环形对称Gabor变换和PCA加权特征的人脸识别算法.首先将人脸图像变换到环形对称Ga-bor变换域,然后在变换域采用PCA加权方法提取分类特征.在3个人脸库上进行实验,与传统人脸识别算法的对比实验说明该算法的可行性和对光照、姿态变化具有更好的鲁棒性.Circularly symmetrical Gabor transforms （CSGT） has two advantageous properties： reduced redundancy and rotation invariance. A face recognition method is proposed based on circularly symmetrical Gabor transforms and weighted PCA feature. The face image is transformed to CSGT, and then the discriminant features for face recognition are extracted using weighted PCA. Detailed theoretical analysis is presented and simulation results on three face databases are given. Comparative experiments of various face recognition schemes are carried out. The experimental results show the feasibility and advantages of the proposed method.

关 键 词：人脸识别 环形对称Gabor变换(CSGT) 主成分分析(PCA) 主成分分析加权 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]