摘要翻译：
人体皮肤检测是对给定图像中肤色像素和区域的识别。由于肤色对方向和大小不变，而且处理速度快，因此在人体皮肤检测中经常使用肤色。本文提出了一种新的人体皮肤检测算法。识别皮肤像素的三个主要参数是RGB（红、绿、蓝）、HSV（色调、饱和度、值）和YCbCr（亮度、色度）颜色模型。该算法的目标是提高给定图像中皮肤像素的识别率。该算法不仅考虑了三个颜色参数的单个范围，而且考虑了AC-Count组合范围，从而提高了图像中皮肤区域的识别精度。
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英文标题：
《Human Skin Detection Using RGB, HSV and YCbCr Color Models》
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作者：
S. Kolkur, D. Kalbande, P. Shimpi, C. Bapat, and J. Jatakia
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最新提交年份：
2017
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Computer Vision and Pattern Recognition        计算机视觉与模式识别
分类描述：Covers image processing, computer vision, pattern recognition, and scene understanding. Roughly includes material in ACM Subject Classes I.2.10, I.4, and I.5.
涵盖图像处理、计算机视觉、模式识别和场景理解。大致包括ACM课程I.2.10、I.4和I.5中的材料。
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一级分类：Quantitative Biology        数量生物学
二级分类：Other Quantitative Biology        其他定量生物学
分类描述：Work in quantitative biology that does not fit into the other q-bio classifications
不适合其他q-bio分类的定量生物学工作
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英文摘要：
  Human Skin detection deals with the recognition of skin-colored pixels and regions in a given image. Skin color is often used in human skin detection because it is invariant to orientation and size and is fast to process. A new human skin detection algorithm is proposed in this paper. The three main parameters for recognizing a skin pixel are RGB (Red, Green, Blue), HSV (Hue, Saturation, Value) and YCbCr (Luminance, Chrominance) color models. The objective of proposed algorithm is to improve the recognition of skin pixels in given images. The algorithm not only considers individual ranges of the three color parameters but also takes into ac- count combinational ranges which provide greater accuracy in recognizing the skin area in a given image.
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PDF链接：
https://arxiv.org/pdf/1708.02694