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1 May 2003 Analysis of a large set of color spaces for skin pixel detection in color images
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Proceedings Volume 5132, Sixth International Conference on Quality Control by Artificial Vision; (2003) https://doi.org/10.1117/12.515148
Event: Quality Control by Artificial Vision, 2003, Gatlinburg, TE, United States
Abstract
Human skin color is a powerful fundamental cue that can be used in particular, at an early stage, for the important applications of face and hand detection in color images, and ultimately, for meaningful human-computer interactions. In this paper, we analyze the distribution of human skin for a large number of three-dimensional (3-D) color spaces (or 2-D chrominance spaces) and for skin images recorded with two different camera systems. By use of seven different criteria, we show that mainly the normalized r-g and CIE-xy chrominance spaces, or spaces constructed as a suitable linear combination or as ratios of normalized r, g and b values, or a space normalized by √R2+G2+B2, are consistently the most efficient for skin pixel detection and consequently, for image segmentation based on skin color. In particular, in these spaces the skin distribution can be modeled by a simple, single elliptical Gaussian, and it is most robust to a change of camera system.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jean-Christophe Terrillon, Arnaud Pilpre, Yoshinori Niwa, and Kazuhiko Yamamoto "Analysis of a large set of color spaces for skin pixel detection in color images", Proc. SPIE 5132, Sixth International Conference on Quality Control by Artificial Vision, (1 May 2003); https://doi.org/10.1117/12.515148
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