关键词: 线性鉴别分析, 人脸识别, 局部方法, 二维线性鉴别分析

Abstract: A Linear Discriminant Analysis method Base on Column（CBLDA） is proposed. CBLDA calculates the projection matrix for each class. Considered the strong symmetry of face images, the selection of the nearest of the column for projection matrix will conquer some variations of illuminations and postures. So the projection matrix should be maximized the between-class nearest columns and minimized the within-class nearest columns. Also, columns are the inner scale of the face image, which will be changed according to the face image resolution. It does not need to decide the size of image block. Experimental results on ORL, FERET and YALE B face databases show that the proposed method is more robust than several state-of-the-art face recognition methods, 2DLDA, 2DLPP and 2DLGEDA.

Key words: Linear Discriminant Analysis（LDA）, face recognition, local method, 2D linear discriminant analysis method