%0 Journal Article
%T Defects and Improvement of Modular Two-dimensional Principal Component Analysis<br>模块2DPCA的缺陷与改进
%A ZHU Minghan
%A LUO Dayong
%A <br>朱明旱
%A 罗大庸
%J 中国图象图形学报
%D 2009
%I 
%X Modular 2DPCA is an extension of 2DPCA algorithm. The recognition performance of modular 2DPCA is more robust than that of 2DPCA.In this paper, the defects of modular 2DPCA about computing the total scatter matrix of training samples and selecting eigenvectors are analyzed. An improved modular 2DPCA algorithm is presented. Experiments show that the improved modular 2DPCA algorithm can select better eigenvectors and extract facial features more effectively.
%K modular two-dimensional principal component analysis
%K eigenvector
%K feature extraction
%K face recognition<br>模块2DPCA
%K 本征向量
%K 特征提取
%K 人脸识别
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D06194629680C940ACE75262F54B9D85&aid=BC2E07E5C0762DF3F7144871E3723986&yid=DE12191FBD62783C&vid=F3583C8E78166B9E&iid=CA4FD0336C81A37A&sid=BB0EA31DB1B01173&eid=10F298ED9F164662&journal_id=1006-8961&journal_name=中国图象图形学报&referenced_num=1&reference_num=12