Comparison of five color models in skin pixel classification

Abstract

Detection of skin in video is an important component of systems for detecting, recognizing, and tracking faces and hands. Different skin detection methods have used different color spaces. This paper presents a comparative evaluation of pixel classification performance of two skin detection methods in five color spaces. The skin detection methods used in this paper are color-histogram based approaches that are intended to work with a wide variety of individuals, lighting conditions, and skin tones. One is the widely-used lookup table method, the other makes use of Bayesian decision theory. Two types of enhancements, based on spatial and texture analyses, are also evaluated.