期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2013
卷号：58
期号：2
出版社：Journal of Theoretical and Applied
摘要：Face recognition is the process of categorizing a person in an image by evaluating with a known face image library. The pose and illumination variations are two main practical confronts for an automatic face recognition system. This paper proposes a novel face recognition algorithm known as EDCA for face recognition under varying poses and illumination conditions. The main aim of this paper is to reduce the feature vector size. The intensity of a face image is normalized to get an illumination normalized image. This EDCA algorithm overcomes the high dimensionality problem in the feature space by extracting features from the low dimensional frequency band of the image. It combines the features of both LDA and PCA algorithms. The experiments were performed on both the Extended Yale B datasets. The experimental results show that the proposed algorithm produces a higher recognition rate than the existing LDA and PCA based face recognition techniques.
关键词：Face Recognition; Histogram Equalization; LDA And PCA
