Dirichlet-based probability model applied to human skin detection [image skin detection]

The performance of a statistical signal processing system depends in large part on the accuracy of the probabilistic model used. This paper presents a robust probabilistic mixture model based on a generalization of the Dirichlet distribution. An unsupervised algorithm for learning this mixture is given, too. The proposed approach for estimating the parameters of a Dirichlet mixture is based on the maximum likelihood (ML) and Fisher scoring methods. Experimental results involve human skin color modeling and its application to skin detection in images.