期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2012
卷号：9
期号：2
出版社：IJCSI Press
摘要：A robust and efficient face recognition system was developed and evaluated. The each individual face is characterized by 2D-DCT coefficients which follows a finite mixture of doubly truncated Gaussian distribution. In modelling the features vector of the face the number of components (in the mixture model) are determined by hierarchical clustering. The model parameters are estimated using EM algorithm. The face recognition algorithm is developed by maximum likelihood under Baysian frame. The method was tested on two available face databases namely JNTUK and yale. The recognition rates computed for different methods of face recognition have revealed that the proposed method performs very well when compared to the other approaches. It is also observed that the proposed system require less number of DCT coefficients in each block and serve well even with large and small databases. The hybridization of hierarchical clustering with model based approach has significantly improved the recognition rate of the system even with the simple features like DCT. Keywords: Face recognition system, doubly truncated Gaussian mixture model, Hierarchical clustering algorithm, DCT coefficients.
