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Proceedings Paper

Face recognition under variable lighting using local qualitative representations
Author(s): Yi Zhang; Ying Chu; Xingang Mou; Guilin Zhang
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Paper Abstract

In this paper, a face recognition method using local qualitative representations is proposed to solve the problem of face recognition in varying lighting. Based on the observation that the ordinal relationship between the average brightness of image regions pair is invariant under lighting changes, Local Binary Mapping is defined as an illumination invariant for face recognition based on Local Binary Pattern descriptor, which extracts the local variance features of an image. For the 'symbol' feature vector, hamming distance is used as similarity measurement. It has been proved that the proposed method can provide the accuracy of 100 percent for subset 2, 3, 4 and 98.89 percent for subset 5 of the Yale facial database B when all images in subset 1 are used as gallery.

Paper Details

Date Published: 15 November 2007
PDF: 7 pages
Proc. SPIE 6788, MIPPR 2007: Pattern Recognition and Computer Vision, 67881L (15 November 2007); doi: 10.1117/12.749831
Show Author Affiliations
Yi Zhang, Huazhong Univ. of Science and Technology (China)
Ying Chu, Huazhong Univ. of Science and Technology (China)
Xingang Mou, Huazhong Univ. of Science and Technology (China)
Guilin Zhang, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 6788:
MIPPR 2007: Pattern Recognition and Computer Vision

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