A recall or precision oriented skin classifier using binary combining strategies

Skin detection is a preliminary step in several applications, and many different methods are available in the literature. We show that the performance of explicit skin cluster classifiers can be enhanced by preprocessing the images with a white balance algorithm. Different combining strategies are then applied to these binary classifiers to further improve their performance in terms of recall and/or precision. Experimental results on a large and heterogeneous image database are presented.