Human skin detection in images by MSER analysis

Human skin detection in images is desirable in many practical applications, e.g., adult-content filtering. However, existing methods are mainly pixel-based and ignore that human skin is region-based. In this paper, we introduce a successful region detector, i.e., MSER, into the skin detection by regarding the skin region as the maximally stable extremal region (MSER). We extend the original MSER to both color and texture analysis to reduce the skinlike regions¹. Furthermore, to be adaptive to the dynamic illumination and chrominance, face detection is used to customize the skin color model to each image. The proposed method has achieved promising performance over our dataset, which is a challenging set with a great part of hard images. Our True Positive Rate is 81.2% under False Positive Rate 8.2%, which outperforms all of eight state-of-the-art algorithms.