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Skin Detection Using Hybrid Colour Space of RGB-H-CMYK

机译:使用RGB-H-CMYK的混合色彩空间进行皮肤检测

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摘要

Skin detection is an essential step in human face detection and/or recognition, using digital image processing techniques. This paper presents a new human skin detection technique, termed as RGB-H-CMYK that uses triple colour spaces of an image, namely RGB (Red, Blue and Green), H (Hue of HSV) and CMYK (Cyan, Magenta, Yellow and Black). In this proposed method, threshold-based rules are applied on RGB, H and CMYK for skin classification. The input image in these three hybrid colour schemes is explored in different combination such as RC (RGB and CMYK), RH (RGB and H) and RHC (RGB and H and CMYK). The RHC_Vote qualifies the current pixel as skin pixel when at least two rules vote for it. The computational merit of this hybrid colour scheme-based skin detection is validated on the real-time dataset and ECU skin database. The average Recall and Accuracy of this method is recorded as 85% and 89%, respectively. This approach is confirmed to have an edge over its competitive methods, as it promises object localization, based on neighbourhood intensities without using the computationally complex approaches such as facial texture and geometric properties.
机译:皮肤检测是人脸检测和/或识别的基本步骤,使用数字图像处理技术。本文提出了一种新的人类皮肤检测技术,称为RGB-H-CMYK,它使用图像的三重色板,即RGB(红色,蓝色和绿色),H(HSV的色调)和CMYK(青色,洋红色,黄色和黑色)。在这种提出的方​​法中,基于阈值的规则在RGB,H和CMYK上应用皮肤分类。在不同组合中探讨了这三种混合颜色方案中的输入图像,例如RC(RGB和CMYK),RH(RGB和H)和RHC(RGB和H和CMYK)。当至少两个规则投票时,RHC_VOTE将当前像素作为皮肤像素符合其。在实时数据集和ECU皮肤数据库上验证了基于混合体方案的皮肤检测的计算优点。该方法的平均召回和准确性分别记录为85%和89%。这种方法被确认在其竞争方法中具有优势,因为它基于邻域强度,而不使用诸如面部纹理和几何属性的计算复杂方法。

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