Human Identification Using Finger Images
Human Identification Using Finger Images
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DOI：
10.1109/tip.2011.2171697
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发表时间：
2012-04-01
影响因子：
10.6
通讯作者：
Zhou, Yingbo
中科院分区：
文献类型：
--
作者：
Kumar, Ajay;Zhou, Yingbo
本文提出了一种新的方法来提高手指静脉识别系统的性能。该系统同时获取手指静脉和低分辨率指纹图像，并使用一种新的分数级组合策略将这两种证据组合在一起。我们研究了以前提出的手指静脉识别方法，并开发了一种新的方法，证明了它比以前发表的努力的优越性。检查从网络摄像头获取的低分辨率指纹图像的效用，以确定从这些图像中匹配的性能。我们开发和研究了两种新的分数级融合方法，即整体融合和非线性融合，并与更流行的分数级融合方法进行了比较评估，以确定它们在所提出的系统中的有效性。在156个受试者的6264幅图像数据库上的严格实验结果表明，无论是在认证实验还是识别实验中，该算法的性能都有了显著的提高。
This paper presents a new approach to improve the performance of finger-vein identification systems presented in the literature. The proposed system simultaneously acquires the finger-vein and low-resolution fingerprint images and combines these two evidences using a novel score-level combination strategy. We examine the previously proposed finger-vein identification approaches and develop a new approach that illustrates it superiority over prior published efforts. The utility of low-resolution fingerprint images acquired from a webcam is examined to ascertain the matching performance from such images. We develop and investigate two new score-level combinations, i.e., holistic and nonlinear fusion, and comparatively evaluate them with more popular score-level fusion approaches to ascertain their effectiveness in the proposed system. The rigorous experimental results presented on the database of 6264 images from 156 subjects illustrate significant improvement in the performance, i.e., both from the authentication and recognition experiments.