Title of Paper:Shadow determination and compensation for face recognition

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Date of Publication:2014-08-01

Journal:INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS

Included Journals:SCIE、EI、Scopus

Volume:5

Issue:4

Page Number:599-605

ISSN No.: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.