Mobile Contactless Fingerprint Recognition: Implementation, Performance and Usability Aspects

This work presents an automated contactless fingerprint recognition system for smartphones. We provide a comprehensive description of the entire recognition pipeline and discuss important requirements for a fully automated capturing system. In addition, our implementation is made publicly available...

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Published inSensors (Basel, Switzerland) Vol. 22; no. 3; p. 792
Main Authors Priesnitz, Jannis, Huesmann, Rolf, Rathgeb, Christian, Buchmann, Nicolas, Busch, Christoph
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 20.01.2022
MDPI
Subjects
Algorithms
Automation
Biometric identification
biometric performance
Biometrics
Cameras
contactless fingerprint
Coronaviruses
COVID-19
Databases, Factual
fingerprint recognition
Humans
Medical research
Pandemics
SARS-CoV-2
Severe acute respiratory syndrome coronavirus 2
Smartphones
Usability
User feedback
biometric performance
biometrics
contactless fingerprint
usability
fingerprint recognition
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Abstract This work presents an automated contactless fingerprint recognition system for smartphones. We provide a comprehensive description of the entire recognition pipeline and discuss important requirements for a fully automated capturing system. In addition, our implementation is made publicly available for research purposes. During a database acquisition, a total number of 1360 contactless and contact-based samples of 29 subjects are captured in two different environmental situations. Experiments on the acquired database show a comparable performance of our contactless scheme and the contact-based baseline scheme under constrained environmental influences. A comparative usability study on both capturing device types indicates that the majority of subjects prefer the contactless capturing method. Based on our experimental results, we analyze the impact of the current COVID-19 pandemic on fingerprint recognition systems. Finally, implementation aspects of contactless fingerprint recognition are summarized.
AbstractList This work presents an automated contactless fingerprint recognition system for smartphones. We provide a comprehensive description of the entire recognition pipeline and discuss important requirements for a fully automated capturing system. In addition, our implementation is made publicly available for research purposes. During a database acquisition, a total number of 1360 contactless and contact-based samples of 29 subjects are captured in two different environmental situations. Experiments on the acquired database show a comparable performance of our contactless scheme and the contact-based baseline scheme under constrained environmental influences. A comparative usability study on both capturing device types indicates that the majority of subjects prefer the contactless capturing method. Based on our experimental results, we analyze the impact of the current COVID-19 pandemic on fingerprint recognition systems. Finally, implementation aspects of contactless fingerprint recognition are summarized.
This work presents an automated contactless fingerprint recognition system for smartphones. We provide a comprehensive description of the entire recognition pipeline and discuss important requirements for a fully automated capturing system. In addition, our implementation is made publicly available for research purposes. During a database acquisition, a total number of 1360 contactless and contact-based samples of 29 subjects are captured in two different environmental situations. Experiments on the acquired database show a comparable performance of our contactless scheme and the contact-based baseline scheme under constrained environmental influences. A comparative usability study on both capturing device types indicates that the majority of subjects prefer the contactless capturing method. Based on our experimental results, we analyze the impact of the current COVID-19 pandemic on fingerprint recognition systems. Finally, implementation aspects of contactless fingerprint recognition are summarized.This work presents an automated contactless fingerprint recognition system for smartphones. We provide a comprehensive description of the entire recognition pipeline and discuss important requirements for a fully automated capturing system. In addition, our implementation is made publicly available for research purposes. During a database acquisition, a total number of 1360 contactless and contact-based samples of 29 subjects are captured in two different environmental situations. Experiments on the acquired database show a comparable performance of our contactless scheme and the contact-based baseline scheme under constrained environmental influences. A comparative usability study on both capturing device types indicates that the majority of subjects prefer the contactless capturing method. Based on our experimental results, we analyze the impact of the current COVID-19 pandemic on fingerprint recognition systems. Finally, implementation aspects of contactless fingerprint recognition are summarized.
Author Busch, Christoph
Priesnitz, Jannis
Rathgeb, Christian
Huesmann, Rolf
Buchmann, Nicolas
AuthorAffiliation 1 da/sec—Biometrics and Internet Security Research Group, Hochschule Darmstadt, Schöfferstraße 8b, 64295 Darmstadt, Germany; christian.rathgeb@h-da.de (C.R.); christoph.busch@h-da.de (C.B.)
3 Fraunhofer AISEC, Breite Straße 12, 14199 Berlin, Germany; nicolas.buchmann@aisec.fraunhofer.de
2 UCS—User-Centered Security Research Group, Hochschule Darmstadt, Schöfferstraße 8b, 64295 Darmstadt, Germany; rolf.huesmann@h-da.de
AuthorAffiliation_xml – name: 3 Fraunhofer AISEC, Breite Straße 12, 14199 Berlin, Germany; nicolas.buchmann@aisec.fraunhofer.de
– name: 1 da/sec—Biometrics and Internet Security Research Group, Hochschule Darmstadt, Schöfferstraße 8b, 64295 Darmstadt, Germany; christian.rathgeb@h-da.de (C.R.); christoph.busch@h-da.de (C.B.)
– name: 2 UCS—User-Centered Security Research Group, Hochschule Darmstadt, Schöfferstraße 8b, 64295 Darmstadt, Germany; rolf.huesmann@h-da.de
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Keywords biometric performance
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contactless fingerprint
usability
fingerprint recognition
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Snippet This work presents an automated contactless fingerprint recognition system for smartphones. We provide a comprehensive description of the entire recognition...
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SubjectTerms Algorithms
Automation
Biometric identification
biometric performance
Biometrics
Cameras
contactless fingerprint
Coronaviruses
COVID-19
Databases, Factual
fingerprint recognition
Humans
Medical research
Pandemics
SARS-CoV-2
Severe acute respiratory syndrome coronavirus 2
Smartphones
Usability
User feedback
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Title Mobile Contactless Fingerprint Recognition: Implementation, Performance and Usability Aspects
URI https://www.ncbi.nlm.nih.gov/pubmed/35161540
https://www.proquest.com/docview/2627837139
https://www.proquest.com/docview/2629055583
https://pubmed.ncbi.nlm.nih.gov/PMC8839666
https://doaj.org/article/fb79579d5f7f419cab3e6e2db9414835
Volume 22
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