Department of Computing, The Hong Kong Polytechnic University, Hung Hom, Hong Kong.
IEEE Trans Image Process. 2012 Apr;21(4):2228-44. doi: 10.1109/TIP.2011.2171697. Epub 2011 Oct 13.
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.
本文提出了一种新的方法来提高文献中提出的手指静脉识别系统的性能。所提出的系统同时获取手指静脉和低分辨率指纹图像，并使用新颖的分数级组合策略将这两种证据结合起来。我们检查了先前提出的手指静脉识别方法，并开发了一种新方法，证明其优于先前发表的工作。检查从网络摄像头获取的低分辨率指纹图像的实用性，以确定此类图像的匹配性能。我们开发并研究了两种新的分数级组合，即整体和非线性融合，并将它们与更流行的分数级融合方法进行比较评估，以确定它们在提出的系统中的有效性。在来自 156 个主体的 6264 个图像的数据库上呈现的严格实验结果表明，性能有了显著提高，即身份验证和识别实验都是如此。
