VPID: Towards Vein Pattern Identification Using Thermal Imaging
Art der Publikation: Beitrag in Zeitschrift
| Autor(en): | Sarah Faltaous, Jonathan Liebers; Yomna Abdelrahman, Florian Alt; Schneegass, Stefan |
|---|---|
| Titel der Zeitschrift: | i-com |
| Heftnummer: | 18 (3) |
| Seiten: | 259-270 |
| Veröffentlichung: | 2019 |
| ISSN: | 1618-162X |
| Digital Object Identifier (DOI): | doi:10.1515/icom-2019-0009 |
| Volltext: | VPID: Towards Vein Pattern Identification Using Thermal Imaging (6,62 MB) |
| Zitation: | Download BibTeX |
Kurzfassung
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.