A modified NLDA algorithm

Null space linear discriminant analysis (NLDA) and linear discriminant analysis based on generalized singular value decomposition (LDA/GSVD) are two popular linear discriminant analysis (LDA) methods that can solve Small Sample Size (SSS) problem. In this paper we present the relation between NLDA and LDA/GSVD under a mild condition, and propose a modified NLDA (MNLDA) algorithm. By both theoretical analysis and experimental results on ORL and FERET face databases, the proposed MNLDA has been proved to have the same discriminating power as LDA/GSVD and to be more efficient than LDA/GSVD.