Detecting Skin Colors under Varying Illumination
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.
skin color detection varying illumination color constancy color correction
Leyuan Liu Rui Huang Saiyong Yang Nong Sang
National Key Laboratory of Science and Technology on Multi-spectral Information Processing, Institut National Key Laboratory of Science and Technology on Multi-spectral Information Processing,Institute
国际会议
桂林
英文
1-7
2011-11-01（万方平台首次上网日期，不代表论文的发表时间）