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Multi-Perspective Enrolment in Finger Vein Recognition

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 deals with the identification of subjects based on its venous pattern within the fingers. The majority of the scanner devices capture a single finger from the palmar side using light transmission. Some of them are equipped with a contact surface or other structures to support in finger placement. However, these means are not able to prevent all possible types of finger misplacements, in particular longitudinal finger rotation can not be averted. It has been shown that this type of deformation causes severe problems to finger vein recognition systems. Multi-perspective enrolment tries to overcome the problem of longitudinal finger rotation by acquiring multiple perspectives during enrolment and comparing this perspectives to a single perspective acquired during recognition. If enough perspectives are involved, the system can even be made invariant against longitudinal finger rotation.


[Prommegger20a  ] Advanced Multi-Perspective Enrolment in Finger Vein Recognition Bernhard Prommegger, Andreas Uhl In Proceedings of the 8th International Workshop on Biometrics and Forensics (IWBF'20), pp. 1-6, Porto, Portugal, April 29 - April 30

Data Sets

PLUSVein Finger Rotation Data Set

The PLUSVein Finger Rotation Data Set (PLUSVein-FR) is a partly publically available finger vein data set. It contains finger images captured all around the finger from 63 different subjects, 4 fingers (index and middle finger from both hands) per subject, which sums up to a total of 252 unique fingers. Further information regarding the data set can be found by the following link:

PLUSVein-FR Data Set

Evaluation Framework Information

The experimental evaluations have been conducted using the open source vein recognition framework (PLUS OpenVein Finger- and Hand-Vein Toolkit) provided by the University of Salzburg. This is a feature extraction and matching/evaluation framework for finger- and hand-vein recognition implemented in MATLAB. It was tested on MATLAB 2016 and should work with all version of MATLAB newer or equal to 2016. This software is under the Simplified BSD license.

A more detailed description of the framework as well as its sources can be found here:

PLUS OpenVein Finger- and Hand-Vein Toolkit

The framework contains all the feature extraction, comparison as well as evaluation methods used for the experiments in the paper.


Coming soon ...

Coming soon ...