Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/37674
Title: Face recognition based on illumination restoration
Authors: Liu , D
Shen , L
Lam, KM 
Kong, X
Keywords: Edge detection
Face recognition
Image segmentation
Iterative methods
Lighting
Principal component analysis
Issue Date: 2004
Source: Proceedings of the International Symposium on Intelligent Multimedia, Video and Speech Processing (ISIMP’2004), Hong Kong, 20-22 Oct. 2004, p. 105-108 How to cite?
Abstract: Variations in lighting conditions make face recognition an even more challenging and difficult task. In this paper, a novel approach is proposed to handle the illumination problem. Our method can restore a face image captured under arbitrary lighting conditions to one with frontal illumination by using a ratio-image and an iterative algorithm. The restored images with frontal illumination are used for face recognition by means of PCA. Experimental results demonstrate that our method can achieve a higher recognition rate, based on the Yale B and Yale database. Moreover, our algorithm has several advantages over other previous algorithms: (1) it does not need to estimate the face surface normals and the light source directions; (2) it does not need many images captured under different lighting conditions for each person, nor a set of bootstrap images that includes many images with different illuminations; and (3) it does not need to detect accurate positions of some facial feature points and to warp the image for alignment, etc.
URI: http://hdl.handle.net/10397/37674
ISBN: 0-7803-8687-6
DOI: 10.1109/ISIMP.2004.1434011
Appears in Collections:Conference Paper

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