Face Recognition based on Modular 2DPCA and Contextual Constraints based Kernel Discriminant Analysis

摘要：

　　In this paper,an improved face recognition algorithm is proposed based on the combination of modular 2DPCA and contextual constraints based kernel discriminant analysis (CCKDA) because of the disadvantages of CCLDA.CCLDA first transforms an image matrix to a vector which caused high dimeusionality and computational complexity and not considers the local feature.While our method first extracts the local features with the original images which are divided into modular sub-images,then CSKDA is utilized,which incorporates the contextual information into kernel discriminant analysis.Experimental results obtained on ORL and XM2VTS databases show the effectiveness of the new method.

关键词： M2DPCA CCLDA CCKDA face recognition

作者: Hua-Li Feng

作者单位: Educational Informatization Centre Wuxi Institute of Commerce Wuxi,China

会议类型: 国际会议

会议名称: 2013 2nd International Conference on Computer Science and Electronics Engineering(ICCSEE2013)(2013年第二届计算机科学与电子工程国际会议)

会议地点: 杭州

会议语种:英文

页码: 1839-1842

在线出版日期: 2013-03-22（万方平台首次上网日期，不代表论文的发表时间）