Pixel based skin colour classification exploiting explicit skin cluster definition methods

In this paper we examine the performance, on a large and heterogeneous image database, of various skin detectors based on explicit colour skin cluster definition, coupled with a cast remover to see whether, and to what degree, the effectiveness of classification is improved, regardless of the strategy adopted. We also evaluate the hypothesis that a combination of some of the skin detection algorithms studied could ensure a more accurate classification than any of the algorithms provides individually. Different combination rules have been investigated. All the experiments have been performed on the Compaq skin database. The results are evaluated in terms of both recall (the ratio between the number of skin pixels correctly classified and the total number of actual skin pixels), and precision (the ratio between the number of skin pixels correctly classified and the total number of pixels labelled as skin pixels by the detection method employed).