Low—dimensional feature representation with enhanced discriminatory power is of paramount importance to face recognition(FR)system．Linear Discriminant Analysis(LDA)is one of the most popular linear classification techniques of feature extraction。but it will meet two problems as computational challenging and “small sample size’’when applying to face recognition directly．After studying people solve the two problems through several ways and realize the face recogni— tion based on LDA． The short paper here makes compare on theory and experimental data analysis on several Face Recognition system using LDA—Based Algorithm，such as Eigenfaces(using PCA)，Fisherfaces，DLDA，VDLDA and VD— FLDA．The experimental results show that the VDFLDA method is the best of al1．

基于LDA算法的人脸识别方法的比较研究.PDF

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