HAND DORSAL VEIN RECOGNITION BY MATCHING WIDTH SKELETON MODELS

This paper proposes a novel and efficient shape-based approach for hand dorsal vein recognition. A coarse-to-fine segmentation method is first introduced to precisely detect the boundaries of the vein areas. A generalized graph model, namely Width Skeleton Model (WSM), is built then, which takes both the topology of the vein network and the width of the vessel into account, thereby achieving more comprehensive geometric representation and conveying more discriminative cues for identification. The models of different samples are further efficiently compared through a new matching scheme for similarity measurement, based on which the identity of the individual is finally decided. We evaluate the proposed approach on the NCUT database, and the rank-one recognition rate reaches 99.31%, which is superior to the state of the arts, clearly illustrating its competency.