Method to extract features of face image combined SVD and LDA

A new method to extract features of face image based on singular value decomposition(SVD) and linear discriminant analysis(LDA) is proposed.First,the mean image of all train samples is selected as a standard face image,and all the train samples are projected into the two orthogonal matrixes which come form the SVD of the standard face image.Then the left-top information of projecting coefficient matrix is extracted as the primary feature.Finally,LDA is used to extracted the recognition feature.In this method,the problem of the equivalent basis space with SVD used into face recognition is resolved,at the same time,class information of samples is added and problem of small sample with LDA is abolished.ORL and CAS-PEAL database are used to test,the experimental results show the method is effective and its insensitivity to the illumination change.