Modified Algorithm of Two-Dimension LDA for Face Recognition

摘要：

A modified two-dimension linear discriminant analysis (2DLDA) algorithm is proposed.After lighting compensation,the input face images are processed first by singular value decomposition (SVD) perturbation and wavelet transform,and then the 2DLDA is used to extract the features,whose dimension is further reduced by PCA algorithm.At last,the support vector machines (SVM) classifier is used for classification and recognition.Experimental results on ORL database show that the proposed method has better recognition performance than other PCA-and LDA-based algorithms.

作者: Yanjiang Wang Juan Fang Peng Suo

作者单位: College of Information and Control Engineering,China University of Petroleum,Dongying,Shandong 257061,P.R.China

会议类型: 国际会议

会议名称: 9th International Conference on Signal Processing(第九届国际信号处理学术会议)(ICSP08)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-26（万方平台首次上网日期，不代表论文的发表时间）