Face recognition based on complete orthogonal neighbourhood preserving discriminant embedding

Abstract

In order to address Small Sample Size( SSS) problem encountered by Neighbourhood Preserving Discriminant Embedding( NPDE) and make full use of the discriminant information in the null space and non-null space of withinneighbourhood scatter matrix for face recognition, this paper proposed a Complete Orthogonal Neighbourhood Preserving Discriminant Embedding( CONPDE) algorithm for face recognition. The algorithm firstly removed the null space of the total neighbourhood scatter matrix using eigen decomposition method indirectly. Then, the optimal discriminant vectors were extracted in the null space and non-null space of within-neighbourhood scatter matrix, respectively. Besides, to further improve the recognition performance, the orthogonal projection matrix obtained based on economic QR decomposition was given. The experiments on ORL and Yale face database show the efficiency of the proposed method.