(2D)2PCA plus (2D)2LDA A new feature extraction for face recognition

摘要：

In this paper, we combine the advantages of (2D)2PCA and (2D)2LDA, and propose a two-stage framework: (2D)2PCA+(2D)2LDA. In the first stage, a twodirectional 2D feature extraction technique. (2D) 2PCA, is employed to condense the dimension of image matrix; in the second stage, the two-directional 2D linear discriminant analysis (2D)2LDA is performed in the (2D):PCA subspace to find the optimal discriminant feature vectors. In addition, the proposed method can take full advantage of the descriptive information and discriminant information of the image. Experiments conducted on ORL and Yale face databases demonstrate the effectiveness and robustness of the proposed method.

关键词： Face recognition Feature extraction (2D)2PCA (2D)2LDA

作者: Guohong Huang

作者单位: Faculty of Information Engineering, Guangdong University of Technology, Guangzhou 510006,P.R.China

会议类型: 国际会议

会议名称: Third International Conference on Digital Image Processing(ICDIP 2011)(第三届数字图像处理国际会议)

会议地点: 成都

会议语种:英文

页码: 605-608

在线出版日期: 2011-04-15（万方平台首次上网日期，不代表论文的发表时间）