[an error occurred while processing this directive] Multimedia Signal Processing and Security Lab
home  |   research   |  members   |  projects  |  publications   |  conferences of interest   |  downloads   |  contact  |  intern

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.


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).


The download files are available upon request.

Please fill out this form to request a download link for the scores and settings files:

Email address: