Improved-LDA based face recognition using both facial global and local information

To achieving higher classification rate under various conditions is challenging task in face recognition community. This paper presents a combined feature Fisher classifier ((CFC)-C-2) approach for face recognition, which is robust to moderate changes of illumination, pose and facial expression. The novelty of the method are: (1) the facial combined feature used for face representation, which is derived from facial global and local information extracted by DCT and (2) the development of Fisher classifier for high-dimensional multi-classes problem. Experiments on ORL and Yale face databases show that the proposed approach is superior to the traditional methods such as Eigenfaces and Fisherfaces. (c) 2005 Elsevier B.V. All rights reserved.