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SKIN DETECTION USING COLOR PROCESSING MECHANISM INSPIRED BY THE VISUAL SYSTEM

机译:使用视觉系统启发的颜色处理机制皮肤检测

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Skin detection is an important procedure for face detection, hand gesture analysis, and objectionable image filtering. In this paper, a skin detection algorithm is proposed according to the colour processing mechanism inspired by the visual system. In the algorithm different types of neurons are used to deal with skin colour and texture. Inspired by receptive fields of rod, cone and orientation selectivity neurons in the visual system, a neural network is proposed to identify skin area in an image. The network contains three types of cones, one type of rod and four types of orientation neurons. Three cones are in response to red, green and blue lights respectively. The rods are in response to brightness. Orientation neurons are used to detect textures of skin. Through their specific receptive fields, the network can be trained to identify skin areas. The experimental results show that the proposed algorithm is comparable to current skin segmentation algorithms.
机译:皮肤检测是面部检测,手势分析和令人反感的图像过滤的重要程序。在本文中,根据由视觉系统启发的颜色处理机制提出了一种皮肤检测算法。在算法中,不同类型的神经元用于处理肤色和纹理。灵感来自视觉系统中的杆,锥形和取向选择性神经元的接受领域,提出了一种神经网络来识别图像中的皮肤区域。网络含有三种类型的锥体,一种杆和四种类型的定向神经元。三个锥体分别响应红色,绿色和蓝色光。杆响应亮度。定向神经元用于检测皮肤纹理。通过其特定的接收领域,可以培训网络以识别皮肤区域。实验结果表明,该算法与当前的皮肤分割算法相当。

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