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Super-Resolution and Image Re-Projection for Iris Recognition
Federal University of Tocantins, Palmas, Brazil.
Department of Computer Sciences at Salzburg University, Salzburg, Austria.
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.ORCID iD: 0000-0002-1400-346X
2019 (English)In: 2019 IEEE 5th International Conference on Identity, Security, and Behavior Analysis (ISBA), 2019, p. 1-7Conference paper, Published paper (Refereed)
Abstract [en]

Several recent works have addressed the ability of deep learning to disclose rich, hierarchical and discriminative models for the most diverse purposes. Specifically in the super-resolution field, Convolutional Neural Networks (CNNs) using different deep learning approaches attempt to recover realistic texture and fine grained details from low resolution images. In this work we explore the viability of these approaches for iris Super-Resolution (SR) in an iris recognition environment. For this, we test different architectures with and without a so called image re-projection to reduce artifacts applying it to different iris databases to verify the viability of the different CNNs for iris super-resolution. Results show that CNNs and image re-projection can improve the results specially for the accuracy of recognition systems using a complete different training database performing the transfer learning successfully.

Place, publisher, year, edition, pages
2019. p. 1-7
Series
IEEE International Conference on Identity, Security and Behavior Analysis (ISBA), ISSN 2640-5555, E-ISSN 2640-0790 ; 5
Keywords [en]
Iris recognition, Databases, Image resolution, Training, Deep learning, Image reconstruction, Image recognition
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:hh:diva-38507DOI: 10.1109/ISBA.2019.8778581ISBN: 978-1-7281-0532-1 (electronic)ISBN: 978-1-7281-0531-4 (electronic)ISBN: 978-1-7281-0533-8 (print)OAI: oai:DiVA.org:hh-38507DiVA, id: diva2:1268696
Conference
Fifth IEEE International Conference on Identity, Security and Behavior Analysis (ISBA), Hyderabad, India, 22-24 January, 2019
Funder
EU, Horizon 2020, 700259
Note

Funding: the European Union’s Horizon 2020 research and innovation program under grant agreement No 700259. This research was partially supported by CNPq-Brazil for Eduardo Ribeiro under grant No. 00736/2014-0.

Available from: 2018-12-06 Created: 2018-12-06 Last updated: 2019-08-15Bibliographically approved

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Alonso-Fernandez, Fernando

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf