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  • P329 - BIOSIG 2022 - Proceedings of the 21st International Conference of the Biometrics Special Interest Group
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Cross-Sensor Finger Vein Recogition

Author:
Bernhard Prommegger, Georg Wimmer and Andreas Uhl [DBLP]
Abstract
If biometric systems are rolled out on a large scale, it will not always be guaranteed that all capturing devices are of exactly the same type. It is therefore important to ensure that the biometric system also works across multiple capturing devices. In finger vein biometry, there is almost no published work in this regard. The biggest problem here is certainly that there are only very few datasets (recorded by different institutions) that usually have no overlap at all with the test persons contained. In a first approach, this article tries to examine how well cross-sensor finger vein recognition works. For the investigation, four publicly available datasets, which were acquired with four different devices in three different scenarios, were evaluated. Using three different finger vein recognition approaches, we will show that the results distinctly deteriorate in cross-sensor recognition scenarios compared to the recognition results using only images from the same device, even more so for image data from contact-less and contact-based capturing devices
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Bernhard Prommegger, G. W., (2022). Cross-Sensor Finger Vein Recogition. In: Brömme, A., Damer, N., Gomez-Barrero, M., Raja, K., Rathgeb, C., , ., Todisco, M. & Uhl, A. (Hrsg.), BIOSIG 2022. Bonn: Gesellschaft für Informatik e.V.. (S. 253-260). DOI: 10.1109/BIOSIG55365.2022.9896962
@inproceedings{mci/Bernhard Prommegger2022,
author = {Bernhard Prommegger, Georg Wimmer and Andreas Uhl},
title = {Cross-Sensor Finger Vein Recogition},
booktitle = {BIOSIG 2022},
year = {2022},
editor = {Brömme, Arslan AND Damer, Naser AND Gomez-Barrero, Marta AND Raja, Kiran AND Rathgeb, Christian AND Sequeira Ana F. AND Todisco, Massimiliano AND Uhl, Andreas} ,
pages = { 253-260 } ,
doi = { 10.1109/BIOSIG55365.2022.9896962 },
publisher = {Gesellschaft für Informatik e.V.},
address = {Bonn}
}
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More Info

DOI: 10.1109/BIOSIG55365.2022.9896962
ISBN: 978-3-88579-723-4
ISSN: 1617-5493
xmlui.MetaDataDisplay.field.date: 2022
Language: en (en)
Content Type: Text/Conference Paper

Keywords

  • Finger Vein Recognition
  • Cross-Sensor Recognition
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  • P329 - BIOSIG 2022 - Proceedings of the 21st International Conference of the Biometrics Special Interest Group [35]

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Diese Digital Library basiert auf DSpace.

 

 


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Gesellschaft für Informatik e.V. (GI), Kontakt: Geschäftsstelle der GI
Diese Digital Library basiert auf DSpace.