A Markov Random Field based skin detection approach

A new color space is used in this paper together with a Markov Random Field model for the detection of skin pixels in colored images. The proposed color space is derived through the principal component analysis technique thus reducing the number of color components. The MRF model takes into account the spatial relations within the image that are included in the labeling process through statistical dependence among neighboring pixels. Since only two classes are considered the Ising model is used to perform the skin/non-skin classification process.