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Finger Vein Recognition with Classical Fingerprint Minutiae Comparison Techniques

This is "The Multimedia Signal Processing and Security Lab", short WaveLab, website. We are a research group at the Computer Sciences Department of the University of Salzburg headed by Andreas Uhl. The short name "WaveLab" already indicates that wavelets are among our favorite tools - we have 15 years of experience in this area. Our research is focused on Multimedia Security including Watermarking, Image and Video Compression, Medical Image Classification, and Biometrics.

Abstract

Finger vein recognition is a biometric authentication method which utilizes vein patterns of human fingers. In classical approaches a correlation-based template comparison using segmented vein pattern is employed. However, analogous to fingerprint recognition so called minutiae points, defined by branchings of veins, can be used as a trait for recognition tasks. The intention of this work is to show how classical minutiae-based fingerprint comparison software performs on finger vein minutiae. A publicly available and two commercial software packages are used to evaluate the recognition performance on three publicly available databases. The results indicate that minutia-based comparison technology from fingerprint recognition can successfully be applied on finger vein recognition and compete with the classical correlation-based methods utilized in the field of vein recognition.

Software Information

Software written in C++ (Cxx11). Needs the opencv library (Tested with 3.4.2). Is a CMake project (requires CMake version 3.4).

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