Double-orientation code and nonlinear matching scheme for palmprint recognition

Many palmprint authentication approaches have been proposed in recent years. Among them, the orientation based coding approach, in which the dominant orientation features of palmprints are extracted and encoded into bitwise codes, is one of the most promising approaches. The distance between codes created from two palmprint images is calculated in the matching stage. Reliable orientation feature extraction and efficient matching are the two most crucial problems in orientation based coding approaches. However, conventional coding based approaches usually extract only one dominant orientation feature by adopting filters with discrete orientations, which is sensitive to the noise and rotation. This paper proposed a novel double-orientation code (DOC) scheme to represent the orientation feature of palmprint and designed an effective nonlinear angular matching score to evaluate the similarity between the DOC. Extensive experiments performed on three types of palmprint databases demonstrate that the proposed approach has excellent performance in comparison with previously proposed state-of-the-art approaches.