An Efficient Reformative Kernel Discriminant Analysis for Face Recognition

An efficient reformative kernel discriminant analysis, namely enhanced kernel discriminant analysis (EKDA), is proposed in this paper. In the proposed algorithm, a novel criterion, i.e., maximizing the class separability both in the feature space and in the projection subspace, is presented to enhance the discriminant power of KDA. EKDA is more adaptive to… (More)