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Finger Vein Template Protection based on Alignment-Robust Feature Description and Index-of-Maximum Hashing | |||||||
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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Finger Vein Template Protection based on Alignment-Robust Feature Description and Index-of-Maximum HashingSeveral algorithms have been used for protecting the used finger vein images that have been investigated in the scope of the IEEE Transactions on Biometrics, Behavior, and Identity Science paper "Finger Vein Template Protection based on Alignment-Robust Feature Description and Index-of-Maximum Hashing". The corresponding information to these implementations, necessary setting-files and recognition result files can be downloaded from this site to comply with the principles of reproducible research. AbstractPrivacy preserving storage and secure processing of biometric data is a key issue that has to be addressed in finger vein recognition systems as well. Various template protection approaches originally proposed for well established biometric modalities have been adopted to the domain of finger vein authentication. However, these adopted methods have the disadvantage that they are not designed for finger vein patterns in particular and are thus, sub-optimal in several ways. In this study we propose an alignment-robust template protection scheme that is based on an efficient binary representation of finger vein patterns on the one hand and is further using the advantages of Index-of-Maximum (IoM) hashing to fulfill mandatory privacy and security based characteristics on the other hand. The proposed method is compared to block re-mapping and warping regarding recognition performance and is analyzed with respect to security and privacy aspects. The analysis is further extended to robustness against misalignment of the finger vein data and a combination of block re-mapping/warping and the proposed method is investigated as well. Reference[Kirchgasser19d ] Finger Vein Template Protection based on Alignment-Robust Feature Description and Index-of-Maximum Hashing IEEE Transactions on Biometrics, Behavior, and Identity Science 2:4, pp. 337-349, 2020
Data SetsPLUSVein-FV3 Finger Vein Data SetThe PLUSVein-FV3 Finger Vein Data Set (PLUSVein-FV3) is a publically available finger vein data set. It contains palmar and dorsal images of 360 fingers from 60 different subjects (ring, middle and index finger from both hands) captured in one session with five samples per finger using two different variants of the same sensor: One utilizing NIR laser modules for illumination, the other one using NIR LEDs. Further information regarding the data set can be found by the following link: University of Twente Finger Vascular Pattern DatabaseThe University of Twente Finger Vascular Pattern (UTFVP) Database is a publically available finger vein data set. It contains six fingers (ring, middle and index finger from both hands) from 60 volunteers acquired in two sessions. Further information regarding the data set can be found by the following link: UTFVP Download Page (external link) Template Protection Framework InformationTwo resources can be downloaded to obtain the entire code used to perform the experiments:
Evaluation Framework InformationThe 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 ToolkitThe framework contains all the feature extraction, comparison as well as evaluation methods used for the experiments in the paper. Result Files and SettingsTwo resources can be downloaded to obtain the entire code used to perform the experiments:
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