Abstract
Hand detection is the first step of any hand biometric recognition process, which determines the outcome of the following treatments. In this study, the authors propose a robust method for hand detection without contact and without constraints on the capture environment. This method is based on a data-mining process for skin-colour modelling. The presented data-mining process offers several advantages like the choice of the most relevant colour axes and the automatic choice of the decision rules. To improve the achieved results of skin detection and to determine the hand region in the image, a succession of postprocessings was proposed. The authors hand detection method was evaluated experimentally on a real database, namely, Sfax-Miracl hand database'; the outcomes of this evaluation show promising results and demonstrate the effectiveness of the proposed method.