全手多实例指静脉生物识别系统

H. N. Mohamed, E. A. El-Alamy, M. K. Shahin
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引用次数: 2

摘要

本文介绍了一门通过结合每个人的多个手指静脉模式来提高手指静脉生物识别系统准确性和性能的学科。我们不再只有一根手指,而是从右手和左手各获得两根手指来代表一个身份。首先对每个手指区域进行分割,然后利用图像轮廓中的最大曲率点提取每个手指的静脉树;采用相位相关(POC)技术对单个手指的二元静脉模式进行匹配。采用评分水平融合方法从属于单一身份的多个手指静脉模式中获得单一决策。所设计的系统可以考虑用于认证和识别目的。与现有的几种多模态系统相比,该系统的优点是在感官层面上很难欺骗攻击,并且近红外FV热图像是活体检测和确保的良好信号。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Whole-hands multiple-instances finger vein biometric system
This paper introduces a discipline to improve the finger vein biometric system accuracy and performance by incorporating multiple finger vein patterns for each person. Instead of just a single finger, we acquired 2 fingers from the right hand and 2 from the left hand to represent a single identity. Firstly, each finger region was segmented then the vein tree for each finger was extracted using maximum curvature points in image profiles. The binary vein pattern for each single finger was matched using the phase only correlation (POC) technique. The score level fusion methodologies were used to obtain a single decision from multiple finger vein patterns belonging to a single identity. The designed system can be considered for authentication and identification purposes. Advantages of this system over few existing multimodal systems are its being very hard to spoof attacks on the sensory level and the NIR FV thermal images are good signals for liveness detection and ensuring.
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