%0 Journal Article
%T Face recognition based on curvelet and PCA<br>基于曲波与主分量分析的人脸识别
%A ZHANG Jiu-long
%A ZHANG Zhi-yu
%A QU Xiao-e
%A ZHAO Yang
%A SHI Zheng-hao
%A <br>张九龙
%A 张志禹
%A 屈小娥
%A 赵阳
%A 石争浩
%J 计算机应用
%D 2008
%I 
%X A new method combining curvelet transform and principal components analysis (PCA) is presented for face recognition. Considering the disadvantage of wavelet, say, it is only optimal in representing point singularities, we use curvelet transform to extract facial features. The facial features being mostly curves, curvelet transform directly takes edges for representation, resulting in a more powerful feature extraction. PCA is then used to map the feature into more meaningful subspace, hence we get higher recognition rate. The experiments demonstrate the effectiveness of the proposed method.
%K curvelet transform
%K Principal Components Analysis (PCA)
%K face recognition
%K anisotropy<br>曲波变换
%K 主分量分析
%K 人脸识别
%K 各向异性
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=0D70A665D119E99249F5B880824447CE&yid=67289AFF6305E306&vid=D3E34374A0D77D7F&iid=94C357A881DFC066&sid=EB4DE9DC132993F4&eid=CDE97535A1E7BEA0&journal_id=1001-9081&journal_name=计算机应用&referenced_num=0&reference_num=12