To search, Click below search items.


All Published Papers Search Service


Face Recognition Based on Kernel Principal Components Analysis and Proximal Support Vector Machine


Li Yunfeng, Sun Lihua


Vol. 12  No. 9  pp. 59-62


High order statistics of the original data can be handled by Kernel Principal Components Analysis, which can describe multiple correlations between pixels in the image recognition, at the same time the nonlinear features of the image can be preferably extracted. Support Vector Machine has a better ability of nonlinear mapping and a stronger generalization capability, while the Proximal Support Vector Machine is an improvement for Support Vector Machine. In this paper, the computer simulation was progressed based on ORL face database, the effectiveness of the Proximal Support Vector Machine algorithm and Kernel Principal Components Analysis algorithm were shown by experimental results..


Kernel Principal Components Analysis, Support Vector Machine, Proximal Support Vector Machine, face recognition