计算机工程与应用2017，Vol.53Issue(13)：211-215,222,6.DOI:10.3778/j.issn.1002-8331.1602-0061
基于列最近邻的线性鉴别分析方法及应用
Linear discriminant analysis method based on column for face recognition
摘要
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 maxi-mized 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.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Key words
Linear Discriminant Analysis(LDA)/face recognition/local method/2D linear discriminant analysis method分类
信息技术与安全科学引用本文复制引用
黄伟,王晓辉,江玉珍..基于列最近邻的线性鉴别分析方法及应用[J].计算机工程与应用,2017,53(13):211-215,222,6.基金项目
2016年广东省自然科学基金-粤东西北创新人才联合培养项目(No.2016A030307050) （No.2016A030307050）
2016年广东省公益能力研究项目(No.2016A020225008) （No.2016A020225008）
2014年潮州市哲学社会科学"十二五"规划重点项目(No.2014-D-02). （No.2014-D-02）
