Abstract
Direction features server as one of the most important features of palmprint and there have been a number of direction-based palmprint recognition methods. However, most existing direction-based methods extract the dominant direction features, which are possibly not the most discriminative features due to the influence of the neighboring directions. In this paper, we present a straightforward example to show that the direction with a large neighboring direction response difference (NDRD) is more stable so as to be more robust and discriminative. Inspired by that, we propose a new feature descriptor by extracting multiple direction features with the competitive NDRDs for palmprint recognition. Extensive experiments conducted on three widely used palmprint databases, including the PolyU, IITD and CASIA databases, demonstrate the effectiveness of the proposed method.
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