Hand Segmentation for Hand-based Biometrics in Complex Environments

Hand-basedbiometric techniques, such as the ones based on palmprint, hand vein and handshape, is becoming more important because of their convenience and highperformance. Hand segmentation is one of the most important steps in thesetechniques. It is a challenge task to accurately segment hand in complex environment because of the complex background,varying illuminance and other unexpected interference factors. This paperproposes a novel approach to segment hand in complex environment using colorand boundary information. In the proposed approach, the hand skin color model(HSCM) is firstly constructed by using artificial neural network (ANN). Thenthe HSCM is used to generate a probability map (PM) and the hand is roughlysegmented from the complex background by thresholding PM. After that, the handboundary is extracted from the original image by edge detecting and votingtechniques. Finally, the hand boundary is employed to cut the roughly segmentedhand to get the final segmented hand. The experimental results show that theproposed approach can effectively segment hand in complex environment.