Discriminative and Robust Competitive Code for Palmprint Recognition
提出一种基于更精确主方向表示的判别性与鲁棒竞争编码方法，并通过邻域方向信息加权提升精度和稳定性，在三种掌纹数据库和噪声数据集上验证了有效性。
Various palmprint recognition methods have been proposed based on orientation features of palmprints. Among them, the competitive code method using the dominant orientation of palmprint images achieves promising performance in palmprint recognition. In this paper, we propose a discriminative and robust competitive code based method, which uses a more accurate dominant orientation representation of palmprint images for palmprint authentication. Moreover, we propose to weight the orientation information of a neighbor area to improve the precision and stability of the discriminative and robust dominant orientation code. Experiments performed on three types of palmprint databases and a noisy dataset validate the effectiveness of the proposed method.