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The Two Sides of the Finger - Performance of Dorsal vs. Palmar - 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.
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Evaluation Framework InformationThe experimental evaluations have been conducted using the open source vein recognition framework (PLUS OpenVein SDK) 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 SDK
Data SetPLUSVein-FV3 Laser/LED based Dorsal/Palmar Finger Vein Data SetThe finger-vein data set used during the evaluations is publicly available for research and non-commercial purposes and can be requested here: Further informations regarding the data set can be found by following the above link.
Scores FilesGeneral Structure of the FilesThe 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 StructureAccording to the experiments, there are two different sets of score files: one for the laser based scanner and one for the LED based scanner. These sets are further divided by the side of the hand (palmar and dorsal) So the directory structure is as follows:
Each of the subdirectories contains one scores file or one settings file per feature type, respectively:
Scores Files and Settings DownloadThe scores and settings are available upon request. | |||||||
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