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Author Spotlight: Developing a Unique Modular Microphysiological System to Mimic Human Barrier Tissue

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Sweet-An Open Source Modular Platform for Contactless Hand Vascular Biometric Experiments.

David Geissbühler¹, Sushil Bhattacharjee¹, Ketan Kotwal¹

¹Idiap Research Institute, 1920 Martigny, Switzerland.

Sensors (Basel, Switzerland)

|August 28, 2025

Summary

This summary is machine-generated.

This study introduces a contactless vascular biometrics platform for hygienic hand vein and palmprint recognition. The system enables non-contact data acquisition, improving usability in sensitive environments.

Keywords:

finger-vein recognition multi-spectral imaging photometric stereo stereoscopy vascular biometrics

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Area of Science:

Biometrics and Pattern Recognition
Computer Vision
Human-Computer Interaction

Background:

Traditional vein recognition systems require physical contact, posing hygiene challenges.
Contactless biometrics is crucial for applications demanding high sanitation standards.
Existing contactless solutions for vascular biometrics are limited.

Purpose of the Study:

To develop and evaluate a novel contactless vascular biometrics sensor platform.
To enable multi-modal data acquisition for hand vascular and surface features.
To create a new dataset for finger-vein recognition research.

Main Methods:

Developed the 'sweet' contactless sensor platform supporting multi-spectral Near-Infrared (NIR), RGB-color, Stereo Vision (SV), and Photometric Stereo (PS) modalities.
Collected a comprehensive dataset of finger, palm, and wrist vascular data from 120 subjects.
Conducted experiments focusing on Finger-Vein Recognition (FVR) and explored multi-modal fusion techniques.

Main Results:

The contactless platform successfully acquired vascular and surface data from fingers, palms, and wrists.
Experimental results demonstrated the potential of the platform for biometric applications, particularly FVR.
Analysis included the effectiveness of fusing data from multiple acquisition modalities.

Conclusions:

The 'sweet' platform offers a viable contactless solution for vascular biometrics, addressing hygiene concerns.
The newly collected dataset and open-source resources will advance research in contactless biometrics.
Multi-modal fusion shows promise for enhancing the accuracy and robustness of biometric systems.