Research and Improvement on the Algorithm of Face Region Detection Based on Skin Color Model

Abstract:

In face image with complex background, the CbCr skin color region will have offset when considering the illumination change. Therefore, the non-skin color pixels which luminance is less than 80 will be mistaken as skin color pixels and the skin color pixels which luminance is greater than 230 will be mistaken as non-skin color pixels. In order to reduce the misjudgments, an improved skin color model of nonlinear piecewise is put forward in this paper. Firstly, the skin color model of non-piecewise is analyzed and the experimental results show that by this model there is an obvious misjudgment in face detection. Then the skin color model of nonlinear piecewise is mainly analyzed and is demonstrated by mathematics method. A large number of training results show that the skin color model of nonlinear piecewise has better clustering distribution than the skin color model of non-piecewise. At lastly, the face detection algorithm adopting skin color model of nonlinear piecewise is analyzed. The results show that this algorithm is better than the algorithm adopting skin color model of non-piecewise and it makes a good foundation for the application of face image.

• Periodical: Applied Mechanics and Materials (Volumes 543-547)
• Pages: 2702-2705
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.543-547.2702
• Online since: March 2014
• Authors: Hong Hai Liu*, Xiang Hua Hou
• Keywords: Clustering Distribution, Nonlinear Piecewise, Self-Adaption, Skin Color Model

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