Most of the existing techniques for palmprint recognition are based on metrics that evaluate the distance between a pair of features. These metrics are typically based on static functions. In this paper we propose a new technique for palmprint recognition based on a dynamical system approach, focusing on preliminary experimental results. The essential idea is that the procedure iteratively eliminates points in both images to be compared which do not have enough close neighboring points in the image itself and in the comparison image. As a result of the iteration, in each image the surviving points are those having enough neighboring points in the comparison image. Our preliminary experimental results show that the proposed dynamic algorithm is competitive and slightly outperforms some state-of-the-art methods by achieving a higher genuine acceptance rate
