Vascular Biometrics Experiments on Candy -- A New Contactless Finger-Vein Dataset
Type of publication: | Conference paper |
Citation: | Bhattacharjee_ICPR_2024 |
Publication status: | Accepted |
Booktitle: | Proceedings of the International Conference on Pattern Recognition (ICPR) |
Year: | 2024 |
Month: | December |
Location: | Calcutta (India) |
Abstract: | The topic of finger-vein (FV) biometrics is an active and growing topic of research. Most FV systems available today rely on contact sensors that capture vein patterns of a single finger at a time. We have recently completed a project aimed at designing a contactless vein sensing platform, named sweet. In this paper we present a new FV dataset collected using sweet. The dataset includes multiple FV samples from 120 subjects, and 280 presentation attack instruments (PAI), captured in a contactless manner. Further, we present baseline FV authentication (FVA) results achieved for proposed dataset. The sweet platform is equipped to capture a sequence of images suitable for photometric-stereo (PS) reconstruction of 3D surfaces. We present a FV presentation attack detection (PAD) method based on PS reconstruction, and the corresponding baseline FV PAD results on the proposed dataset. |
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Idiap Innosuisse CANDY |
Authors | |
Added by: | [UNK] |
Total mark: | 0 |
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