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The First ICB Competition on Iris Recognition

Authors :
Koichi Noda
Peihua Li
Nadia Othman
Valérian Némesin
Tieniu Tan
Man Zhang
Fernando Alonso-Fernandez
Jing Liu
Akanksha Joshi
Zhenan Sun
Wu Su
Edmundo Hoyle
Center for Research on Intelligent Perception and (Institute of Automation, Chinese Academy of Sciences)
Department of Automation (University of Science and Technology of China)
Zhuhai YiSheng Electronics Technology Co, LDT (.)
Halmstad University
GSM (GSM)
Institut FRESNEL (FRESNEL)
Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS)
Département Electronique et Physique (TSP - EPH)
Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP)
Services répartis, Architectures, MOdélisation, Validation, Administration des Réseaux (SAMOVAR)
Centre National de la Recherche Scientifique (CNRS)
Nihon System Laboratory (.)
Dalian University of Technology
Universidade Federal do Rio de Janeiro (UFRJ)
Centre for Development of Advanced Computing (.)
Centre National de la Recherche Scientifique (CNRS)-École Centrale de Marseille (ECM)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)-École Centrale de Marseille (ECM)-Aix Marseille Université (AMU)
Département Electronique et Physique (EPH)
School of Information and Communication Engineering (Dalian University of Technology)
Source :
Proceedings IJCB 2014 : IEEE/IAPR International Joint Conference on Biometrics, IJCB 2014 : IEEE/IAPR International Joint Conference on Biometrics, IJCB 2014 : IEEE/IAPR International Joint Conference on Biometrics, Sep 2014, Clearwater, Fl, United States. pp.1-6, ⟨10.1109/BTAS.2014.6996292⟩, IJCB
Publication Year :
2014
Publisher :
Högskolan i Halmstad, CAISR Centrum för tillämpade intelligenta system (IS-lab), 2014.

Abstract

International audience; Iris recognition becomes an important technology in our society. Visual patterns of human iris provide rich texture information for personal identification. However, it is greatly challenging to match intra-class iris images with large variations in unconstrained environments because of noises, illumination variation, heterogeneity and so on. To track current state-of-the-art algorithms in iris recognition, we organized the first ICB Competition on Iris Recognition in 2013 (or ICIR2013 shortly). In this competition, 8 participants from 6 countries submitted 13 algorithms totally. All the algorithms were trained on a public database(e.g. CASIA-Iris-Thousand[3]) and evaluated on an unpublished database. The testing results in terms of False Non-match Rate (FNMR) when False Match Rate (FMR) is 0:0001 are taken to rank the submitted algorithms

Details

Language :
English
Database :
OpenAIRE
Journal :
Proceedings IJCB 2014 : IEEE/IAPR International Joint Conference on Biometrics, IJCB 2014 : IEEE/IAPR International Joint Conference on Biometrics, IJCB 2014 : IEEE/IAPR International Joint Conference on Biometrics, Sep 2014, Clearwater, Fl, United States. pp.1-6, ⟨10.1109/BTAS.2014.6996292⟩, IJCB
Accession number :
edsair.doi.dedup.....2ab13fc0979d0009c63c88053b6518da
Full Text :
https://doi.org/10.1109/BTAS.2014.6996292⟩