期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2014
卷号：7
期号：6
页码：369-378
DOI：10.14257/ijsip.2014.7.6.32
出版社：SERSC
摘要：In this paper, based on the study of the Two-Dimensional Principal Component Analysis (2DPCA), Two-Dimensional Principal Component Analysis (2DPCA) and fuzzy set theory, we propose a integrated face recognition algorithm based on wavelet subspace. This method can make good use of the advantages of each single method, and also can make up for the defect of each other. The comparison of the results of the different methods identification effect on the ORL 、 YALE and FERET face database show, the integrated method proposed in this paper improves the recognition rate, and it also reduces the training and classification time as well.
关键词：face recognition; Two-Dimensional Principal Component Analysis (2DPCA); ; Two-Dimensional Linear Discriminant Analysis (2DLDA); fuzzy set theory; feature ; extraction
