计算机工程与应用2011，Vol.47Issue(25)：178-181,219,5.DOI:10.3778/j.issn.1002-8331.2011.25.047
独立环形对称Gabor特征及在人脸识别中的应用
Independent circularly symmetrical Gabor feature for face recognition
摘要
Abstract
This paper presents a new feature extraction method for face recognition using 2D Circularly Symmetrical Gabor Transform (2DCSGT) and Independent Component Analysis (ICA).A circularly symmetrical Gabor feature vector is derived from a set of downsampled circularly symmetrical Gabor wavelet representations of face images.The dimension of the circularly symmetrical Gabor feature vector is reduced by means of Principal Component Analysis (PCA).Independent Circularly Symmetrical Gabor Features (ICSGF) are defined based on Independent Component Analysis.To show the validity of the proposed method, it is applied to face recognition on the ORL.YALE and FERET databases.In particular,the ICSGF method achieves 99.5% correct face recognition accuracy for ORL database,93.33% accuracy for Yale database and 97.14% accuracy for FERET database.Experimental results show that the algorithm is feasible and effective for face recognition.关键词
人脸识别/环形对称Gabor变换(CSGT)/主成分分析(PCA)/独立成分分析(ICA)/最近邻分类器Key words
face recognition/ Circularly Symmetrical Gabor Transform (CSGT)/ Principal Component Analysis (PC A)/ Independent Component Analysis(ICA)/nearest neighbor classifier分类
信息技术与安全科学引用本文复制引用
张亮亮,孙国霞..独立环形对称Gabor特征及在人脸识别中的应用[J].计算机工程与应用,2011,47(25):178-181,219,5.基金项目
山东省自然科学基金(No.Y2(007G04) （No.Y2(007G04）
