The segmentation of different skin colors using the combination of graph cuts and probability neural network

Authors:
Chih-Lyang Hwang;Kai-Di Lu
Affiliations:
Department of Electrical Engineering, National Taiwan University of Science and Technology, Taiwan, R.O.C.;Department of Electrical Engineering, Tamkang University, Taiwan, RO.C.
Venue:
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
Year:
2011

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Abstract

It is known that fixed thresholds mostly fail in two situations as they only search for a certain skin color range: (i) any skin-like object may be classified as skin if skin-like colors belong to fixed threshold range. (ii) any true skin for different races may be mistakenly classified as non-skin if that skin colors do not belong to fixed threshold range. In this paper, a dynamic threshold of different skin colors based on the input image is determined by the combination of graph cuts (GC) and probability neural network (PNN). The compared results among GC, PNN and GC+PNN are presented not only to verify the accurate segmentation of different skin colors but also to reduce the computation time as compared with only using the neural network for the classification of different skin-colors and non-skin-color. In addition, the experimental results for different lighting conditions confirm the usefulness of the proposed methodology.