Skin color detection based super pixel

Skin color has a wide range of applications in the fields such as face recognition and gesture recognition. Many pix-el based skin color detection methods are proposed for now, however, it's not confidence to determine whether it is a skin color just based on single pixel in many case. In this paper, super pixel was adopted to detect skin color. Firstly, color images was segmented by the watershed algorithm to get super pixels and the corresponding ground-truth images; then the features of super pixels was extracted as input data and the ground-truth images was ta-ken as output data; finally, support vector machine and random forests was adopted to train the input data and the output data. Experimental results show that, the method based on the features proposed by this paper using SVM and random forests are both better performance than the method based on single pixel.

[1]  Chee Seng Chan,et al.  A Fusion Approach for Efficient Human Skin Detection , 2012, IEEE Transactions on Industrial Informatics.

[2]  Tan Yee Fan,et al.  A Tutorial on Support Vector Machine , 2009 .

[3]  Javier Ruiz-del-Solar,et al.  Skin detection using neighborhood information , 2004, Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004. Proceedings..

[4]  Christopher J. C. Burges,et al.  A Tutorial on Support Vector Machines for Pattern Recognition , 1998, Data Mining and Knowledge Discovery.

[5]  Nikolaos G. Bourbakis,et al.  A survey of skin-color modeling and detection methods , 2007, Pattern Recognit..

[6]  Jitendra Malik,et al.  Learning a classification model for segmentation , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[7]  Andrew Zisserman,et al.  Hand detection using multiple proposals , 2011, BMVC.

[8]  Tin Kam Ho,et al.  The Random Subspace Method for Constructing Decision Forests , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Allan Hanbury,et al.  Color based skin classification , 2012, Pattern Recognit. Lett..