Combined Fully Contact-Less Finger and Hand Vein Acquisition Device - Evaluation Framework and Scores Files
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.
Evaluation Framework Information
The experimental evaluations have been conducted using the open source vein recognition framework (PLUS OpenVein 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.
The framework contains all the feature extraction and matching as well as evaluation methods used for the experiments in the paper:
A more detailed description of the framework as well as its sources can be found here:
PLUS OpenVein Toolkit
PLUSVein-Contactless Finger and Hand Vein Data Set
The finger and hand vein data set used during the evaluations is publicly available for research and non-commercial purposes and can be requested here:
General Structure of the Files
The scores files are provided as MATLAB .mat files. Each .mat file contains a struct, containing two vectors:
The scores are all similarity scores, i.e. higher scores indicate higher similarity. Thus the genuine scores should be ideally higher than the impostor ones. The scores obtained for the 3 binary features using the Miura matcher are in the range of [0 - 0.5] while the scores obtained for SIFT are in the range of [0 - 1].
File Naming Conventions and Directory Structure
According to the experiments, there are three different sets of score files: one for the light transmission illuminated finger vein images, one for the reflected light 850 nm illuminated hand vein images and one for the reflected light 950 nm illuminated hand vein images.
The directory structure is as follows:
Each of the subdirectories contains one scores file or one settings file per feature type, respectively:
available upon request.