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Skin detection using color processing mechanism inspired by the visual system

机译:使用受视觉系统启发的色彩处理机制进行皮肤检测

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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:皮肤检测是用于面部检测,手势分析和不良图像过滤的重要过程。根据视觉系统激发的色彩处理机制,提出了一种皮肤检测算法。在该算法中,使用了不同类型的神经元来处理肤色和纹理。受视觉系统中视杆,视锥和方向选择性神经元的感受野的启发,提出了一种神经网络来识别图像中的皮肤区域。该网络包含三种类型的视锥细胞,一种类型的视杆和四种类型的定向神经元。三个锥体分别响应红,绿和蓝光。棒是对亮度的响应。定向神经元用于检测皮肤纹理。通过其特定的接受区域,可以训练网络以识别皮肤区域。实验结果表明,该算法与目前的皮肤分割算法具有可比性。

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