Efficient Dilation, Erosion, Opening, and Closing Algorithms
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The CMU Pose, Illumination, and Expression (PIE) Database
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
A Face Detection System Based Skin Color and Neural Network
CSSE '08 Proceedings of the 2008 International Conference on Computer Science and Software Engineering - Volume 01
Face detection with the modified census transform
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
IEEE Transactions on Consumer Electronics
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A novel skin segmentation scheme based on human face illumination feature is proposed in this paper. First, we perform a face detection in order to measure the face position and amount on image, and then analyze each face's illumination feature. According these parameters, we classify the skin pixel and generate skin probability map, and finally fetch out a prefect skin mask for skin segmentation. Experimental results based on common dataset show that the proposed method can achieve 92.83% true positive rate (TPR) with 15.82% false positive rate (FPR), outperforming the traditional GMM skin segmentation method.