An SVD based common matrix method for face recognition: Single image per person

Abstract

Common Matrix (CM) fails to work when there is only one image available in the training set. In this paper, an approach to solve this problem is proposed. By using singular value decomposition (SVD) null space of the image matrices are obtained. By projecting the image matrix onto the null space, common matrices are obtained for each class. After obtaining the common matrices, optimal projection vectors will be those that maximize the total scatter of the common matrices. © 2011 Springer Science+Business Media B.V.