Kumar Ajay, Prathyusha K Venkata
Biometrics Research Laboratory, Indian Institute of Technology Delhi, New Delhi 110016, India.
IEEE Trans Image Process. 2009 Sep;18(9):2127-36. doi: 10.1109/TIP.2009.2023153. Epub 2009 May 15.
This paper presents a new approach to authenticate individuals using triangulation of hand vein images and simultaneous extraction of knuckle shape information. The proposed method is fully automated and employs palm dorsal hand vein images acquired from the low-cost, near infrared, contactless imaging. The knuckle tips are used as key points for the image normalization and extraction of region of interest. The matching scores are generated in two parallel stages: (i) hierarchical matching score from the four topologies of triangulation in the binarized vein structures and (ii) from the geometrical features consisting of knuckle point perimeter distances in the acquired images. The weighted score level combination from these two matching scores are used to authenticate the individuals. The achieved experimental results from the proposed system using contactless palm dorsal-hand vein images are promising (equal error rate of 1.14%) and suggest more user friendly alternative for user identification.
本文提出了一种利用手部静脉图像三角测量法和同时提取指关节形状信息来对个人进行身份验证的新方法。所提出的方法是完全自动化的，并采用从低成本、近红外、非接触式成像获取的手掌背部手部静脉图像。指关节尖端被用作图像归一化和感兴趣区域提取的关键点。匹配分数在两个并行阶段生成：(i) 来自二值化静脉结构中四种三角测量拓扑的分层匹配分数，以及 (ii) 来自所获取图像中由指关节点周长距离组成的几何特征的匹配分数。这两个匹配分数的加权分数级组合用于对个人进行身份验证。使用非接触式手掌背部手部静脉图像的所提出系统取得的实验结果很有前景（等错误率为1.14%），并为用户识别提供了更用户友好的替代方案。
