VPID: Towards Vein Pattern Identification Using Thermal Imaging
| dc.contributor.author | Faltaous, Sarah | |
| dc.contributor.author | Liebers, Jonathan | |
| dc.contributor.author | Abdelrahman, Yomna | |
| dc.contributor.author | Alt, Florian | |
| dc.contributor.author | Schneegass, Stefan | |
| dc.date.accessioned | 2020-01-15T08:34:10Z | |
| dc.date.available | 2020-01-15T08:34:10Z | |
| dc.date.issued | 2019 | |
| dc.description.abstract | Biometric authentication received considerable attention lately. The vein pattern on the back of the hand is a unique biometric that can be measured through thermal imaging. Detecting this pattern provides an implicit approach that can authenticate users while interacting. In this paper, we present the Vein-Identification system, called VPID. It consists of a vein pattern recognition pipeline and an authentication part. We implemented six different vein-based authentication approaches by combining thermal imaging and computer vision algorithms. Through a study, we show that the approaches achieve a low false-acceptance rate (“FAR”) and a low false-rejection rate (“FRR”). Our findings show that the best approach is the Hausdorff distance-difference applied in combination with a Convolutional Neural Networks (CNN) classification of stacked images. | en |
| dc.identifier.doi | 10.1515/icom-2019-0009 | |
| dc.identifier.pissn | 1618-162X | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/31047 | |
| dc.language.iso | en | |
| dc.publisher | De Gruyter | |
| dc.relation.ispartof | i-com: Vol. 18, No. 3 | |
| dc.subject | Thermal imaging | |
| dc.subject | usable security | |
| dc.subject | biometrics | |
| dc.title | VPID: Towards Vein Pattern Identification Using Thermal Imaging | en |
| dc.type | Text/Journal Article | |
| gi.citation.endPage | 270 | |
| gi.citation.publisherPlace | Berlin | |
| gi.citation.startPage | 259 | |
| gi.conference.sessiontitle | Research Article |