Abstract:

In view of the poor performance of face recognition，an improved face recognition method based on singularvalueperturbed is proposed in this paper. Firstly, the singularvalueperturbed is applied to the single image so as to obtain expanded image set. Secondly, the wavelet decomposition is used as the preprocessing method, the lowfrequency face image is chosen as a subimage，and the highorder features are extracted by kernel principal component analysis. Finally, the nearest neighbor classifier is used for identification. The experiment results on ORL and Yale face databases show that the proposed method improves the recognition performance in comparison with the comparative approach.

Key words: face recognition;feature extract;singularvalueperturbed;kernel principal component analysis;wavelet transform;nearest neighbor classifier