%0 Journal Article
%T Dual-space Feature Extraction Algorithm Based on PCA and ICA<br>基于PCA及ICA的双空间特征提取算法
%A WANG Wei-dong
%A HAN Bin
%A YANG Jing-yu
%A <br>王卫东
%A 韩斌 杨静宇
%J 中国图象图形学报
%D 2008
%I 
%X No single subspace feature extraction algorithm outperforms others under all circumstances,but applying dual-space feature extraction algorithm can overcome the limits of single subspace.To increase the recognition rate of classified results,a new dual-space feature extraction algorithm is put forward based on PCA(principal component analysis) and ICA(independent component analysis).The algorithm uses ICA as PCA's complementary space to realize feature extraction.The aim of the algorithm is to re-project the samples into ICA subspace to classify,which are difficult to be classified in PCA subspace.The proposed dual-space extraction algorithm includes two steps.Step 1 is called pre-classify,which uses two classifiers in a single subspace to classify the testing samples.If a testing sample is classified into different classes by two classifiers,it would be added into the new testing samples set.In step 2,the algorithm projects the samples of the new testing samples set into another subspace and classifies them.Then,the recognition results of two subspaces are tested together.The experimental results in ORL and FERET database prove the dual-space feature extraction algorithm outperforms the traditional feature extraction algorithm in recognition rate.
%K dual-space algorithm
%K principal component analysis
%K independent component analysis
%K feature extraction
%K face recognition<br>双空间算法
%K 主成分分析
%K 独立成分分析
%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=98DAABD7E108E28EEC5C3AA45657DE60&yid=67289AFF6305E306&vid=FC0714F8D2EB605D&iid=708DD6B15D2464E8&sid=32ACD60B510B932B&eid=31EF1FA369BC6521&journal_id=1006-8961&journal_name=中国图象图形学报&referenced_num=2&reference_num=11