Understanding and Modelling the Vascular Biometric Imaging Procedure
| dc.contributor.author | Muriel van der Spek and Luuk Spreeuwers | |
| dc.contributor.editor | Brömme, Arslan | |
| dc.contributor.editor | Damer, Naser | |
| dc.contributor.editor | Gomez-Barrero, Marta | |
| dc.contributor.editor | Raja, Kiran | |
| dc.contributor.editor | Rathgeb, Christian | |
| dc.contributor.editor | Sequeira Ana F. | |
| dc.contributor.editor | Todisco, Massimiliano | |
| dc.contributor.editor | Uhl, Andreas | |
| dc.date.accessioned | 2022-10-27T10:19:30Z | |
| dc.date.available | 2022-10-27T10:19:30Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | In near-infrared finger vascular biometric images, several structures are visible, from which the exact origin is unknown. These include the appearance of the vessel projection, and the brightness of the two joints and the dark area between the joints. To understand the origin of these elements, the imaging procedure is mimicked using a simplified mathematical model of the finger. This model creates images similar to real finger vascular images incorporating basic anatomy and optical properties. The vessels appear vague, because the projection is actually a shadow caused by the strong scattering of the bone. The intensity of the finger (besides the vessels) is directly dependent on both tissue consistency (amount of absorption/scattering) and finger anatomy (path length of the photons). This research gives an insight on the vascular imaging procedure and this knowledge can be used in future research on vascular biometric identification, by incorporating additional features from the images. | en |
| dc.identifier.doi | 10.1109/BIOSIG55365.2022.9897048 | |
| dc.identifier.isbn | 978-3-88579-723-4 | |
| dc.identifier.pissn | 1617-5496 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/39706 | |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik e.V. | |
| dc.relation.ispartof | BIOSIG 2022 | |
| dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-329 | |
| dc.subject | Effective attenuation coefficient | |
| dc.subject | Finger vein images | |
| dc.subject | Maximum Curvature | |
| dc.subject | Vascular biometrics | |
| dc.subject | UTFVP dataset | |
| dc.title | Understanding and Modelling the Vascular Biometric Imaging Procedure | en |
| dc.type | Text/Conference Paper | |
| gi.citation.endPage | 284 | |
| gi.citation.publisherPlace | Bonn | |
| gi.citation.startPage | 277 | |
| gi.conference.date | 14.-16. September 2022 | |
| gi.conference.location | Darmstadt | |
| gi.conference.sessiontitle | Further Conference Contributions |
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