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Proceedings Paper

Detecting skin colors under varying illumination
Author(s): Leyuan Liu; Rui Huang; Saiyong Yang; Nong Sang
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Paper Abstract

Skin color has been used as an important cue for various human related computer vision applications. However, detecting skin colors under varying illumination is a challenging task, as the appearance of skin in an image highly depends on the illumination under which the image was taken. To this end, a method for detecting skin colors under varying illumination is proposed in this paper. First, spatial illumination variation is identified and the images are segmented into different regions with different illumination. Each illumination region of color images are corrected base on the illuminant estimated by a local edge-based color constancy algorithm. Then, the corrected images are transformed into a color-space, where statistical results on a skin dataset show that the skin color cluster and non-skin color clusters are separated. Finally, the skin colors are modeled under Bayesian decision framework and classified from non-skin colors. The experimental results show that the proposed method is robust to illumination variations.

Paper Details

Date Published: 6 December 2011
PDF: 7 pages
Proc. SPIE 8004, MIPPR 2011: Pattern Recognition and Computer Vision, 80040N (6 December 2011); doi: 10.1117/12.901776
Show Author Affiliations
Leyuan Liu, Huazhong Univ. of Science and Technology (China)
Rui Huang, Huazhong Univ. of Science and Technology (China)
Saiyong Yang, Huazhong Univ. of Science and Technology (China)
Nong Sang, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 8004:
MIPPR 2011: Pattern Recognition and Computer Vision
Jonathan Roberts; Jie Ma, Editor(s)

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