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Combined Fully Contactless Finger and Hand Vein Capturing Device with a Corresponding Dataset.

Christof Kauba¹, Bernhard Prommegger¹, Andreas Uhl¹

¹Department of Computer Sciences, University of Salzburg, Jakob-Haringer-Str. 2, 5020 Salzburg, Austria.

Sensors (Basel, Switzerland)

|November 21, 2019

Summary

Researchers developed a novel contactless device for capturing finger and hand vein images. This device enables high-quality vascular pattern recognition and provides a new, publicly available dataset for research.

Keywords:

biometric recognition performance evaluation contactless acquisition device finger vein recognition hand vein recognition public vascular pattern dataset

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Area of Science:

Biometrics
Image Acquisition
Pattern Recognition

Background:

Vascular pattern biometrics, especially contactless methods, are increasingly important.
High-quality datasets are crucial for advancing vascular pattern recognition research.
Existing datasets may be limited, necessitating new data acquisition methods.

Purpose of the Study:

To propose and detail a novel contactless capturing device for vascular pattern biometrics.
To enable acquisition of both finger and hand vein images using distinct lighting techniques.
To introduce a new, publicly available dataset for contactless vein recognition research.

Main Methods:

Designed a novel contactless capturing device with detailed technical specifications.
Implemented light transmission for palmar finger vein imaging.
Utilized reflected light for palmar hand vein imaging.

Main Results:

Experimental evaluation confirmed the device's capability for high-quality image acquisition.
Recognition performance using established schemes on the acquired dataset was competitive.
The developed dataset is among the first publicly available contactless finger and hand vein datasets.

Conclusions:

The proposed contactless capturing device is effective for finger and hand vein image acquisition.
The device facilitates good image quality and supports competitive biometric recognition performance.
The release of this dataset will significantly aid future research in contactless vascular biometrics.