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Very Low-Resolution Iris Recognition Via Eigen-Patch Super-Resolution and Matcher Fusion
Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).ORCID-id: 0000-0002-1400-346X
University of Malta, Msida, Malta.
Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).ORCID-id: 0000-0002-4929-1262
2016 (Engelska)Ingår i: 2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS), Piscataway: IEEE, 2016, artikel-id 7791208Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

Current research in iris recognition is moving towards enabling more relaxed acquisition conditions. This has effects on the quality of acquired images, with low resolution being a predominant issue. Here, we evaluate a super-resolution algorithm used to reconstruct iris images based on Eigen-transformation of local image patches. Each patch is reconstructed separately, allowing better quality of enhanced images by preserving local information. Contrast enhancement is used to improve the reconstruction quality, while matcher fusion has been adopted to improve iris recognition performance. We validate the system using a database of 1,872 near-infrared iris images. The presented approach is superior to bilinear or bicubic interpolation, especially at lower resolutions, and the fusion of the two systems pushes the EER to below 5% for down-sampling factors up to a image size of only 13×13.

Ort, förlag, år, upplaga, sidor
Piscataway: IEEE, 2016. artikel-id 7791208
Serie
International Conference on Biometrics Theory Applications and Systems
Nyckelord [en]
Iris recognition, Image resolution, Image reconstruction, Databases, Training, Image recognition, Face
Nationell ämneskategori
Signalbehandling Medicinsk bildbehandling Datorseende och robotik (autonoma system) Mediateknik
Identifikatorer
URN: urn:nbn:se:hh:diva-31747DOI: 10.1109/BTAS.2016.7791208ISI: 000392217100054Scopus ID: 2-s2.0-85011263943ISBN: 978-1-4673-9733-9 (digital)ISBN: 978-1-4673-9734-6 (tryckt)OAI: oai:DiVA.org:hh-31747DiVA, id: diva2:952051
Konferens
8th IEEE International Conference on Biometrics: Theory, Applications, and Systems, Niagara Falls, Buffalo, USA, September 6-9, 2016
Forskningsfinansiär
VetenskapsrådetKK-stiftelsen
Anmärkning

Funding: EU COST Action IC1106. Author F. A.-F. also thanks the Swedish Research Council for funding his research, and the CAISR program of the Swedish Knowledge Foundation.

Tillgänglig från: 2016-08-11 Skapad: 2016-08-11 Senast uppdaterad: 2018-03-22Bibliografiskt granskad

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Av författaren/redaktören
Alonso-Fernandez, FernandoBigun, Josef
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CAISR Centrum för tillämpade intelligenta system (IS-lab)
SignalbehandlingMedicinsk bildbehandlingDatorseende och robotik (autonoma system)Mediateknik

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