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Skin-Detection using Bayes and LAB Space

1. Description

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:

Reference:

[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.

2. How does it work?

3. Result

4. How to set up ?

5. How to train ?

6. How to use ?

7. How to contribute ?