On selecting colour components for skin detection

Abstract

We used a data analysis approach for selecting colour components for skin detection. The criterion for this selection was to achieve a reasonable degree of generalisation and recognition, where skin points exhibit a well defined cluster. After evaluating each component of several colour models, we found that a mixture of components can cope well with such requirements. We list the top components, and from these we select one colour space: H-GY-Wr. A nearly convex area of this space contains 97% of all skin points, whilst it encompasses 5.16% of false positives. Even simple rules over this well-shaped space can achieve a high recognition rate and low overlap to non-skin points. This is a data analysis approach that will help to many skin detection systems.