Orientation features are successfully used in coding-based palmprint recognition methods. In this paper, we propose a discriminative neighboring direction indicator to represent the orientation feature of the palmprint. The neighboring direction indicator feature not only represents the most dominant orientation feature of the palmprint, but also better describes the orientation feature of those points which have double dominant orientations. In addition, the neighboring direction indicator shows good robustness to noise and rotation. Using the neighboring direction indicator, we propose a novel palmprint recognition method. Extensive experiments conducted on three types of palmprint databases demonstrate that the proposed method gives better performance than the existing state-of-the-art orientation-based methods. By using the proposed method, the equal error rate is improved by about 10% for palmprint verification, and the average error rate is reduced by 2.7-14% for palmprint identification with a single training sample. © 2016 IEEE.