COMPARING COLOR AND TEXTURE-BASED ALGORITHMS FOR HUMAN SKIN DETECTION

Locating skin pixels in images or video sequences where people appear has many applications, specially those related to Human-Computer Interaction. Most work on skin detection is based on modelling the skin on different color spaces. This paper explores the use of texture as a descriptor for the extraction of skin pixels in images. For this aim, we analyzed and compared a proposed color-based skin detection algorithm (using RGB, HSV and YCbCr representation spaces) with a texture-based skin detection algorithm which uses a measure called Spectral Variation Coefficient (SVC) to evaluate region features. We showed the usefulness of each skin segmentation feature (color versus texture) under different experiments that compared the accuracy of both approaches (i.e. color and texture) under the same set of hand segmented images.