| 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.identifier.isbn | 978-3-88579-723-4 | |
| dc.identifier.issn | 1617-5496 | |
| dc.identifier.uri | http://dl.gi.de/handle/20.500.12116/39706 | |
| 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.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 | |
| dc.pubPlace | Bonn | |
| mci.reference.pages | 277-284 | |
| mci.conference.sessiontitle | Further Conference Contributions | |
| mci.conference.location | Darmstadt | |
| mci.conference.date | 14.-16. September 2022 | |
| dc.identifier.doi | 10.1109/BIOSIG55365.2022.9897048 | |