In this work, we created a skin detector using Bayes Theorem. For that, we first build a base of examples of "skin" and "non-skin" and let the program learn with it. Then we trained our program to generate a histogram of all training images, by taking the color of the skin using the space CIE LAB colors (A-B components only). For more information on the skin detection methods we used please read the following article:
[Vladimir Vezhnevets , Vassili Sazonov , Alla Andreeva] A Survey on Pixel-Based Skin Color Detection Techniques (2003)
IN PROC. GRAPHICON-2003, pp. 85-92, Moscow, Russia, September 2003
(see section 2 on color spaces and section 3 on the construction of
skin models)
This work is directly inspired by this article, so feel free to read it for ideas and additional explanations for this project.