Contactless hand detection in complex image based on data-mining process

Hand detection is the first step of any hand biometric recognition process, which determines the outcome of the following treatments. In this paper, we propose a robust method for hand detection without contact and without constraints on the capture environment for hand biometric applications. This method is based on a color based approach adopting a non-parametric modeling. Our contribution consists mainly in the choice of the most relevant color axes and the choice of the decision rules automatically using a process of the data-mining as a new philosophy of data processing. To improve the achieved results of skin detection and to determine the hand region in the image, a succession of post-processing was proposed. Our hand detection method was evaluated experimentally on a real database; the outcomes of this evaluation show promising results and demonstrate the effectiveness of the proposed method.