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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 Artificial Intelligence and Human Interfaces (AIHI) Department of the University of Salzburg led by Andreas Uhl. Our research is focused on Visual Data Processing and associated security questions. Most of our work is currently concentrated on Biometrics, Media Forensics and Media Security, Medical Image and Video Analysis, and application oriented fundamental research in digital humanities, individualised aquaculture and sustainable wood industry.

Abstract

Security and privacy is of great interest in biometric systems which can be offered by Match-on-Card (MoC) technology, successfully applied in several areas of biometrics. In finger vein recognition such a system is not available yet. Utilizing minutiae points from vein images in combination with classical minutiae-based fingerprint comparison software offers a great opportunity to integrate vein recognition on MoC systems. In this work a publicly available and two commercial software packages are used to evaluate the recognition performance of vein minutiae on three publicly available databases. The results indicate that minutia-based comparison technology from fingerprint recognition can be applied to finger vein recognition and are able to compete with classical correlation-based methods utilized in this field.

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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Multimedia Signal Processing
and Security Lab
Thursday, 25-Apr-2024 12:42:05 CEST