Palm region extraction for contactless palmprint recognition

Palm region extraction is one of the most important processes in palmprint recognition, since the accuracy of extracted palm regions has a significant impact on recognition performance. Especially in contactless recognition systems, a palm region has to be extracted from a palm image by taking into consideration a variety of hand poses. Most conventional methods of palm region extraction assume that all the fingers are spread and a palm faces to a camera. This assumption forces users to locate his/her hand with limited pose and position, resulting in impairing the flexibility of the contactless palmprint recognition system. Addressing the above problem, this paper proposes a novel palm region extraction method robust against hand pose. Through a set of experiments using our databases which contains palm images with different hand pose and the public database, we demonstrate that the proposed method exhibits efficient performance compared with conventional methods.