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Adaptive skin detection using multiple cues

This paper presents an adaptive approach to skin detection. First, we propose a nonlinear relationship among R, G and B components and use a closed curve to identify the skin cluster region. Then, a split machine is designed that aids the extraction of the pixels with similar low-level features from images. Finally, a nonlinear skin color classifier with an adaptive threshold is developed by analyzing the properties of the extracted pixels in the HSL, YCbCr, YUV and YIQ color spaces. Experimental results show that our proposed method works very well in skin detection.