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首页> 外文会议>Sixth International Conference on Quality Control by Artificial Vision May 19-22, 2003 Gatlinburg, Tennessee, USA >Analysis of a Large Set of Color Spaces for Skin Pixel Detection in Color Images
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Analysis of a Large Set of Color Spaces for Skin Pixel Detection in Color Images

机译：彩色图像中皮肤像素检测的大量颜色空间分析

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摘要

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~2 + G~2 + B~2)~(1/2), 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.
机译：人体肤色是一种有力的基本提示，尤其可以在早期用于面部和手部检测在彩色图像中的重要应用，并最终用于有意义的人机交互。在本文中，我们分析了人体在大量三维（3-D）颜色空间（或2-D色度空间）中的分布以及使用两个不同相机系统记录的皮肤图像的分布。通过使用七个不同的标准，我们显示出主要归一化的rg和CIE-xy色度空间，或构造为合适的线性组合或归一化的r，g和b值之比的空间，或由（R〜2 + G〜2 + B〜2）〜（1/2）始终是皮肤像素检测最有效的方法，因此也是基于肤色的图像分割最有效的方法。特别是，在这些空间中，可以通过简单的单个椭圆高斯模型对皮肤分布进行建模，并且它对于更改摄像头系统最稳定。

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