A New Bayesian Classifier for Skin Detection
Sajad Shirali-Shahreza, Mahta Mousavi · 2008
Skin detection has different applications in computer vision such as face detection, human tracking and adult content filtering. One of the major approaches in pixel based skin detection is using Bayesian classifiers. Bayesian classifiers performance is highly related to their training set. In this paper, we introduce a new Bayesian classifier skin detection method. The main contribution of this paper is creating a huge database to create color probability tables and new method for creating skin pixels data set. Our database consists of about 80000 images containing more than 5 billions pixels. Our tests shows that the performance of Bayesian classifier trained on our data set is better than Compaq data set which is one of the currently greatest data sets.