Skin Detection in Web Imagery: Comparison of Techniques and Proposal

This paper presents a quantitative comparison of the performance of skin detection techniques for a Web-based system. The procedures under analysis employ dimensionality reduction, with or without color correction. We propose a rule for deciding if an image requires color correction and, if needed, which is the best procedure. Geometric rules, parametric methods and histogram-based techniques are compared in terms of accuracy and performance. With the proposed heuristic for color correction, the best performances are achieved by a classifier based on the mixture of two Gaussian laws applied to data projected with principal component analysis and a by a KDD-based rule that operates on the RGB space.