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

Abstract

Vascular pattern based biometric recognition is gaining more and more attention, with a trend towards contactless acquisition. An important requirement for conducting research in vascular pattern recognition are available datasets. These datasets can be established using a suitable biometric capturing device. A sophisticated capturing device design is important for good image quality and, furthermore, at a decent recognition rate. We propose a novel contactless capturing device design, including technical details of its individual parts. Our capturing device is suitable for finger and hand vein image acquisition and is able to acquire palmar finger vein images using light transmission as well as palmar hand vein images using reflected light. An experimental evaluation using several well-established vein recognition schemes on a dataset acquired with the proposed capturing device confirms its good image quality and competitive recognition performance. This challenging dataset, which is one of the first publicly available contactless finger and hand vein datasets, is published as well.

Hand-based multibiometric systems: state-of-the-art and future challenges

“…Furthermore, researching on a more relevant distance metric could potentially be useful for matching purposes. Kauba, Prommegger & Uhl (2019) proposed a contactless device to acquire images corresponding to hand-based biometric modalities, which make use of vein patterns for recognition. The authors collected a dataset for evaluation and also used various methods including Gabor filter, high frequency filtering, and interest point based methods for feature extraction.…”

Biometrics in the Era of COVID-19: Challenges and Opportunities

“…Images of the finger or hand are captured with NIR illumination, since light at NIR frequencies is absorbed differently by hemoglobin and the skin, thereby allowing for the detection of vein patterns. Touchless fingervein and palmvein sensors have been developed [103,104,105], though the lack of any control in the collection process typically significant rotation and translation variation. The quality of the capturing device as well as strategies to compensate for nuisance variation are hence key to the collection of high quality images and reliable performance.…”

Feature-Level Fusion of Finger Vein and Fingerprint Based on a Single Finger Image: The Use of Incompletely Closed Near-Infrared Equipment

“…A total of 100 low-quality finger images were selected from 300 fingers database to calculate the hausdorff distance [13], matching scores for fingerprint and finger vein separately. Then we combined the matching scores based on normalization and weighting techniques [39] to realize score-layer fusion.…”

“…These methods need to acquire images separately and have strict requirements for acquisition devices, so the application scenario is limited [12]. Kauba et al [13] proposed a contactless finger and hand vein integrated capturing device and provided the corresponding dataset. The advantages of a contactless capturing device, the principle of imaging which used light transmission and reflected light to acquire palmar finger vein and hand vein images, as well as the hardware structure and light source design are introduced in this paper.…”