Color-based skin segmentation: An evaluation of the state of the art

Abstract

Skin segmentation is widely used, e.g. in face detection and gesture recognition. In the last years, the number of skin segmentation approaches has grown. However, multiple datasets and varying performance measurements make direct comparison difficult. We address these shortcomings and evaluate 5 threshold-based methods, 5 model-based methods, and 2 region-based state-of-the-art skin segmentation methods. We discuss each algorithm and provide the segmentation performance along with the processing time. All methods are evaluated on the ECU dataset which provides a great amount of training data besides other important attributes.