SWEET - An Open Source Modular Platform for Contactless Hand Vascular Biometric Experiments
| Type of publication: | Journal paper |
| Citation: | Geissbuhler_ARXIV_2024 |
| Publication status: | Published |
| Journal: | arXiv |
| Year: | 2024 |
| Month: | April |
| URL: | https://arxiv.org/abs/2404.093... |
| DOI: | https://doi.org/10.48550/arXiv.2404.09376 |
| Abstract: | Current finger-vein or palm-vein recognition systems usually require direct contact of the subject with the apparatus. This can be problematic in environments where hygiene is of primary importance. In this work we present a contactless vascular biometrics sensor platform named SWEET which can be used for hand vascular biometrics studies (wrist-, palm- and finger-vein) and surface features such as palmprint. It supports several acquisition modalities such as multi-spectral Near-Infrared (NIR), RGB-color, Stereo Vision (SV) and Photometric Stereo (PS). Using this platform we collect a dataset consisting of the fingers, palm and wrist vascular data of 120 subjects and develop a powerful 3D pipeline for the pre-processing of this data. We then present biometric experimental results, focusing on Finger-Vein Recognition (FVR). |
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| Projects |
Idiap Innosuisse CANDY |
| Authors | |
| Added by: | [UNK] |
| Total mark: | 0 |
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