Application of Boolean Kernel Function SVM in Face Recognition

SVM based on Boolean kernel function has outstanding performance in classifying, for the problem of face recognition, recognizing strategies based on MDNF and MPDNF Boolean kernel function SVM are Proposed. Firstly, Karhunen-Loeve transform is employed to get the representation basis of face image set, secondly, the extracted characteristics is translated into 0-1 format, thirdly, SVM based Boolean kernel function are used to classify. The face recognition experiments with ORL face databases show that the proposed methods led to significantly better recognition accuracy compared with traditional PCA method and linear SVM, between the proposed methods, the one based on MPDNF Boolean kernel function get better performance.

[1]  Lipo Wang Support vector machines : theory and applications , 2005 .

[2]  Joachim M. Buhmann,et al.  Distortion Invariant Object Recognition in the Dynamic Link Architecture , 1993, IEEE Trans. Computers.

[3]  Lawrence Sirovich,et al.  Application of the Karhunen-Loeve Procedure for the Characterization of Human Faces , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Azriel Rosenfeld,et al.  Face recognition: A literature survey , 2003, CSUR.

[5]  Ping Wang,et al.  Research on Face Recognition Based on Boolean Kernel SVM , 2008, 2008 Fourth International Conference on Natural Computation.

[6]  Lipo Wang,et al.  Data Mining With Computational Intelligence , 2006, IEEE Transactions on Neural Networks.

[7]  Daewon Lee,et al.  An improved cluster labeling method for support vector clustering , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.