A Novel Face Recognition Algorithm with Support Vector Machine Classifier
نویسندگان
چکیده
A novel face recognition algorithm based on Gabor texture information is proposed in this paper. Two strategies to capture it are Gabor Magnitude-based Texture Representation (GMTR) which is characterized by using the Gamma density to model the Gabor magnitude distribution and Gabor Phase-based Texture Representation (GPTR), characterized by using the Generalized Gaussian Density (GGD) to model the Gabor phase distribution. The estimated model parameters serve as texture representation. Experiments are performed on Yale, ORL and FERET databases to validate the feasibility of the method. The results show that GMTR based and GPTR-based SVM classifier both significantly outperform the widely used Gabor energy based systems and other existing subspace methods.
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