%0 Journal Article
%T Application of Principal Component Analysis to Palmprint Images Recognition
主成分分析法在掌纹图像识别中的应用
%A CAI Ping-Sheng
%A YAN Le-Lin
%A
蔡平胜
%A 闫乐林
%J 计算机系统应用
%D 2010
%I
%X The palmprint recognition is a new biometric technology, which has a good prospect of applications in the areas of network security, identity authentication etc. In this paper, the principal component analysis method is applied to palmprint image feature extraction, and the differences between the traditional principal component analysis(PCA) and the weighted principal component analysis(WPCA) in addressing the palmprint image are explained. According to the experimental results of two methods on two databases, PCA has a higher precision of palmprint recognition than WPCA, and the affection of light condition is weakened by WPCA.
%K biometric recognition
%K parmprint recognition
%K PCA
%K WPCA
生物特征识别
%K 掌纹识别
%K 主成分分析
%K 加权主成分分析
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D4F6864C950C88FFCE5B6C948A639E39&aid=76F2301644D300BE1D3B6B390960E92A&yid=140ECF96957D60B2&vid=2A8D03AD8076A2E3&iid=9CF7A0430CBB2DFD&sid=3E0812ED84A7B31D&eid=6235172E4DDBA109&journal_id=1003-3254&journal_name=计算机系统应用&referenced_num=0&reference_num=7