Human skin segmentation improved by texture energy under superpixels

Abstract

Several applications demand the segmentation of images in skin and non-skin regions, such as face recognition, hand gesture detection, nudity recognition, among others. Human skin detection is still a challenging task and, although color attribute is a very important clue, it usually generates high rate of false positives. This work proposes and analyzes a skin segmentation method improved by texture energy. Experimental results on a challenging public data set demonstrate significant improvement of the proposed skin segmentation method over color-based state-of-the-art approaches.