Hand dorsal vein recognition by matching Width Skeleton Models
Hand dorsal vein recognition by matching Width Skeleton Models
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DOI：
10.1109/icip.2016.7532939
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发表时间：
2016-08
期刊：
影响因子：
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通讯作者：
Xiaoxia Li;Di Huang;Renke Zhang;Yunhong Wang;Xianbo Xie
中科院分区：
文献类型：
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作者：
Xiaoxia Li;Di Huang;Renke Zhang;Yunhong Wang;Xianbo Xie
本文提出了一种新的和有效的基于形状的手背静脉识别方法。首先采用由粗到细的分割方法精确地检测静脉区域的边界。然后建立了一个广义的图模型，即宽度骨架模型（WSM），它同时考虑了静脉网络的拓扑结构和血管的宽度，从而实现了更全面的几何表示，并传达了更多的鉴别线索。通过一种新的相似性度量匹配方案，进一步有效地比较不同样本的模型，并最终确定个体的身份。我们在NCUT数据库上对所提出的方法进行了评估，一级识别率达到99.31%，这是上级的艺术状态，清楚地说明了它的能力。
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.