Combined Fully Contactless Finger and Hand Vein Capturing Device with a Corresponding Dataset
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 capturi...
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doaj-74a36e71eb7a49139be93e871deb02652020-11-25T02:21:51ZengMDPI AGSensors1424-82202019-11-011922501410.3390/s19225014s19225014Combined Fully Contactless Finger and Hand Vein Capturing Device with a Corresponding DatasetChristof Kauba0Bernhard Prommegger1Andreas Uhl2Department of Computer Sciences, University of Salzburg, Jakob-Haringer-Str. 2, 5020 Salzburg, AustriaDepartment of Computer Sciences, University of Salzburg, Jakob-Haringer-Str. 2, 5020 Salzburg, AustriaDepartment of Computer Sciences, University of Salzburg, Jakob-Haringer-Str. 2, 5020 Salzburg, AustriaVascular 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.https://www.mdpi.com/1424-8220/19/22/5014finger vein recognitionhand vein recognitioncontactless acquisition devicepublic vascular pattern datasetbiometric recognition performance evaluation |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Christof Kauba Bernhard Prommegger Andreas Uhl |
spellingShingle |
Christof Kauba Bernhard Prommegger Andreas Uhl Combined Fully Contactless Finger and Hand Vein Capturing Device with a Corresponding Dataset Sensors finger vein recognition hand vein recognition contactless acquisition device public vascular pattern dataset biometric recognition performance evaluation |
author_facet |
Christof Kauba Bernhard Prommegger Andreas Uhl |
author_sort |
Christof Kauba |
title |
Combined Fully Contactless Finger and Hand Vein Capturing Device with a Corresponding Dataset |
title_short |
Combined Fully Contactless Finger and Hand Vein Capturing Device with a Corresponding Dataset |
title_full |
Combined Fully Contactless Finger and Hand Vein Capturing Device with a Corresponding Dataset |
title_fullStr |
Combined Fully Contactless Finger and Hand Vein Capturing Device with a Corresponding Dataset |
title_full_unstemmed |
Combined Fully Contactless Finger and Hand Vein Capturing Device with a Corresponding Dataset |
title_sort |
combined fully contactless finger and hand vein capturing device with a corresponding dataset |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2019-11-01 |
description |
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. |
topic |
finger vein recognition hand vein recognition contactless acquisition device public vascular pattern dataset biometric recognition performance evaluation |
url |
https://www.mdpi.com/1424-8220/19/22/5014 |
work_keys_str_mv |
AT christofkauba combinedfullycontactlessfingerandhandveincapturingdevicewithacorrespondingdataset AT bernhardprommegger combinedfullycontactlessfingerandhandveincapturingdevicewithacorrespondingdataset AT andreasuhl combinedfullycontactlessfingerandhandveincapturingdevicewithacorrespondingdataset |
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1724865096285421568 |