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Super-Resolution for Selfie Biometrics: Introduction and Application to Face and Iris
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
University of Malta, Msida, Malta.ORCID iD: 0000-0001-8106-9891
Universidad Autonoma de Madrid, Madrid, Spain.ORCID iD: 0000-0002-6343-5656
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.ORCID iD: 0000-0002-4929-1262
2019 (English)In: Selfie Biometrics: Advances and Challenges / [ed] Ajita Rattani, Reza Derakhshani & Arun A. Ross, Cham: Springer, 2019, 1, p. 105-128Chapter in book (Refereed)
Abstract [en]

Biometric research is heading towards enabling more relaxed acquisition conditions. This has effects on the quality and resolution of acquired images, severly affecting the accuracy of recognition systems if not tackled appropriately. In this chapter, we give an overview of recent research in super-resolution reconstruction applied to biometrics, with a focus on face and iris images in the visible spectrum, two prevalent modalities in selfie biometrics. After an introduction to the generic topic of super-resolution, we investigate methods adapted to cater for the particularities of these two modalities. By experiments, we show the benefits of incorporating super-resolution to improve the quality of biometric images prior to recognition. © Springer Nature AG 2019

Place, publisher, year, edition, pages
Cham: Springer, 2019, 1. p. 105-128
Series
Advances in Computer Vision and Pattern Recognition, ISSN 2191-6586, E-ISSN 2191-6594 ; 77
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:hh:diva-38508DOI: 10.1007/978-3-030-26972-2_5Libris ID: z8pbp2xpw3p1fc6vISBN: 978-3-030-26971-5 (print)ISBN: 978-3-030-26972-2 (electronic)OAI: oai:DiVA.org:hh-38508DiVA, id: diva2:1268697
Projects
SIDUS-AIR
Funder
Swedish Research CouncilVinnovaKnowledge Foundation
Note

Other funder: CogniMetrics (TEC2015-70627-R) from MINECO/FEDER

Available from: 2018-12-06 Created: 2018-12-06 Last updated: 2019-10-16Bibliographically approved

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Alonso-Fernandez, FernandoBigun, Josef

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