Title: Analysis of a large set of color spaces for skin pixel detection in color images
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 √R<sup>2</sup>+G<sup>2</sup>+B<sup>2</sup>, 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.
Publication Year: 2003
Publication Date: 2003-04-30
Language: en
Type: article
Indexed In: ['crossref']
Access and Citation
Cited By Count: 6
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