Analysis of Human Skin Color Images for a Large Set of Color Spaces and for Different Camera Systems
Analysis of Human Skin Color Images for a Large Set of Color Spaces and for Different Camera Systems
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针对大量颜色空间和不同相机系统的人类肤色图像分析
DOI：
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发表时间：
2002
期刊：
影响因子：
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通讯作者：
Kazuhiko Yamamoto
中科院分区：
文献类型：
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作者：
J. Terrillon;Arnaud Pilpré;Y. Niwa;Kazuhiko Yamamoto
人类的肤色是一个强大的基本线索，在早期阶段，它可以特别用于彩色图像中面部和手部检测的重要应用，并最终用于有意义的人机交互。在本文中，我们分析了大量的色彩空间和两种不同的相机系统记录的皮肤图像的人体皮肤的分布。通过使用7种不同的标准，我们表明，主要是归一化的r-g和CIE-xy空间，或者由归一化的r， g和b值的适当线性组合构建的空间，是最有效的基于肤色的图像分割。特别是，他们允许使用一个简单的，单高斯皮肤色度模型，他们产生最稳健的皮肤分布的相机系统的变化。
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 [1] [2], and ultimately, for meaningful human-computer interactions. In this paper, we analyze the distribution of human skin for a large number of 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 spaces, or a space constructed with a suitable linear combination of normalized r, g and b values, are the most efficient for skin color-based image segmentation. In particular, they allow the use of a simple, single Gaussian skin chrominance model, and they yield the most robust skin distribution to a change of camera system.