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  4. Liveness Detection Competition - Noncontact-based Fingerprint Algorithms and Systems (LivDet-2023 Noncontact Fingerprint)
 
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2023
Conference Paper
Title

Liveness Detection Competition - Noncontact-based Fingerprint Algorithms and Systems (LivDet-2023 Noncontact Fingerprint)

Abstract
Liveness Detection (LivDet) is an international competition series open to academia and industry with the objective to assess and report state-of-the-art in Presentation Attack Detection (PAD). LivDet-2023 Noncontact Fingerprint is the first edition of the noncontact fingerprint-based PAD competition for algorithms and systems. The competition serves as an important benchmark in noncontact-based fingerprint PAD, offering (a) independent assessment of the state-of-the-art in noncontact-based fingerprint PAD for algorithms and systems, and (b) common evaluation protocol, which includes finger photos of a variety of Presentation Attack Instruments (PAIs) and live fingers to the biometric research community (c) provides standard algorithm and system evaluation protocols, along with the comparative analysis of state-of-the-art algorithms from academia and industry with both old and new android smartphones. The winning algorithm achieved an APCER of 11.35% averaged over all PAIs and a BPCER of 0.62%. The winning system achieved an APCER of 13.0.4%, averaged over all PAIs tested over all the smartphones, and a BPCER of 1.68% over all smartphones tested. Four-finger systems that make individual finger-based PAD decisions were also tested. The dataset used for competition will be available, to all researchers as per data share protocol. https://noncontactfingerprint2023.1ivdet.org/index.php
Author(s)
Purnapatra, Sandip
Clarkson University
Rezaie, Humaira
Clarkson University
Jawade, Bhavin
University at Buffalo
Liu, Yu
Clarkson University
Pan, Yue
Clarkson University
Brosell, Luke
Clarkson University
Sumi, Mst Rumana
Clarkson University
Igene, Lambert
Clarkson University
Dimarco, Alden
Clarkson University
Setlur, Srirangaraj
University at Buffalo
Dey, Soumyabrata
Clarkson University
Schuckers, Stephanie
Clarkson University
Huber, Marco  orcid-logo
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Kolf, Jan Niklas  
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Fang, Meiling  
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Damer, Naser  
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Adami, Banafsheh
West Virginia University
Chitic, Raul
Dermalog
Seelert, Karsten
Dermalog
Mistry, Vishesh
Tech5
Parthe, Rahul
Tech5
Kacar, Umit
Tech5
Mainwork
IEEE International Joint Conference on Biometrics, IJCB 2023  
Project(s)
Next Generation Biometric Systems  
Next Generation Biometric Systems  
Funder
Bundesministerium für Bildung und Forschung -BMBF-  
Hessisches Ministerium für Wissenschaft und Kunst -HMWK-  
Conference
International Joint Conference on Biometrics 2023  
DOI
10.1109/IJCB57857.2023.10448970
Language
English
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Keyword(s)
  • Branche: Information Technology

  • Research Line: Computer vision (CV)

  • Research Line: Human computer interaction (HCI)

  • Research Line: Machine learning (ML)

  • LTA: Interactive decision-making support and assistance systems

  • LTA: Machine intelligence, algorithms, and data structures (incl. semantics)

  • LTA: Generation, capture, processing, and output of images and 3D models

  • Biometrics

  • Machine learning

  • Spoofing attacks

  • Fingerprint recognition

  • ATHENE

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