Title :
Face Recognition Based on Support Vector Machines
Author :
Jiang Li-Li ; Liang Kun ; Ye Shuang
Author_Institution :
Dept. of Basic, Anhui Sanlian Univ., Hefei, China
Abstract :
Face recognition is the research focus of machine vision, pattern recognition and other areas. It has broad application prospects. in this paper, we apply wavelet transform to human face image preprocessing in order to reduce the impact of expression change on face recognition. then we follow PCA method, mapping the original face image to Eigen-faces axis which mutually orthogonal to achieve dimensionality reduction of eigen. Finally we use support vector machine classification model to identify the projection vector of human face image in the eigen faces axis. the experiment results on the ORL and Yale face databases show that the method is feasible.
Keywords :
eigenvalues and eigenfunctions; face recognition; principal component analysis; support vector machines; wavelet transforms; ORL; PCA method; Yale face databases; eigen-faces axis; face recognition; human face image preprocessing; machine vision; pattern recognition; projection vector identification; support vector machine classification model; support vector machines; wavelet transform; Computational intelligence; face recognition; principal component analysis; support vector machine; wavelet transform;
Conference_Titel :
Computational Intelligence and Design (ISCID), 2012 Fifth International Symposium on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-2646-9
DOI :
10.1109/ISCID.2012.37