A Validity Measure for Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Statistical color models with application to skin detection
International Journal of Computer Vision
Skin Patch Detection in Real-World Images
Proceedings of the 24th DAGM Symposium on Pattern Recognition
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Pattern Recognition, Third Edition
Pattern Recognition, Third Edition
On cluster validity for the fuzzy c-means model
IEEE Transactions on Fuzzy Systems
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In this paper, a new region-based algorithm for detecting skin color in static images is described. We choose the single Gaussian skin color model in the normalized r-g space after analyzing the distributions of skin color in six different 2-D chrominance spaces. Images are first segmented into patches using a improved fuzzy C-means algorithm, in which the local characteristic is adopted to constrain fuzzy functions, and a simple method for initializing clustering centriods is adopted. Then, the percentage of skin color pixels in each patch can be obtained. According to corresponding percentages, patches are classified as skin color regions or not.