Indexed by:Journal Article

Date of Publication:2014-08-01

Journal:INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS

Included Journals:Scopus、EI、SCIE

Volume:5

Issue:4

Page Number:599-605

ISSN:1868-8071

Key Words:Face recognition; Illumination variation; Shadow compensation; Robust PCA; Low-dimensional

Abstract:Illumination variation that occurs on face images will significantly influence the performance of the recognition. Based on the low-dimensional intrinsic of face images, we design a novel two-step shadow compensation method for face recognition. Three indexes are proposed and employed to distinguish the shaded-images. Then, we compensate the shadows adaptively by using a modified Robust PCA result. Experimental results on Yale database and Yale B database demonstrate that the proposed approach can improve the recognition rate. Showing our method is suitable for face recognition with illumination variations.