Beard and mustache segmentation using sparse classifiers on self-quotient images

T. Hoang Ngan Le, Khoa Luu, Keshav Seshadri, Marios Savvides

Abstract: In this paper, we propose a novel system for beard and mustache detection and segmentation in challenging facial images. Our system first eliminates illumination artifacts using the self-quotient algorithm. A sparse classifier is then used on these self-quotient images to classify a region as either containing skin or facial hair. We conduct experiments on the MBGC and color FERET databases to demonstrate the effectiveness of our proposed system.