University of Oulu

Jukka Komulainen ; Abdenour Hadid ; Matti Pietikäinen 2017 Contact lens detection in iris images. In: Christian Rathgeb ; Christoph Busch (eds.) Iris and Periocular Biometric Recognition. The Institution of Engineering and Technology. pp. 265-290. https://doi.org/10.1049/PBSE005E_ch12.

Contact lens detection in iris images

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Author: Komulainen, Jukka; Hadid, Abdenour; Pietikäinen, Matti
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.8 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe201801222182
Language: English
Published: Institution of engineering and technology, 2017
Publish Date: 2018-01-22
Description:

Abstract

Iris texture provides the means for extremely accurate uni-modal person identification. However, the accuracy of iris-based biometric systems is sensitive to the presence of contact lenses in acquired sample images. This is especially true in the case of textured (cosmetic) contact lenses that can be effectively used to obscure the original iris texture of a subject and consequently to perform presentation attacks. Since also transparent contact lenses can degrade matching rates, automatic detection and classification of different contact lens types is needed in order to improve the robustness of iris-based biometric systems. This chapter introduces the problem of contact lens detection with particular focus on cosmetic contact lenses. The state of the art is analysed thoroughly and a case study on generalised textured contact lens detection is provided. The potential future research directions are also discussed.

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ISBN: 978-1-78561-169-8
ISBN Print: 978-1-78561-168-1
Pages: 265 - 290
DOI: 10.1049/PBSE005E_ch12
OADOI: https://oadoi.org/10.1049/PBSE005E_ch12
Host publication: Iris and periocular biometric recognition
Host publication editor: Rathgeb, Christian
Busch, Christoph
Type of Publication: A3 Book chapter
Field of Science: 113 Computer and information sciences
Subjects:
Funding: The financial support of Academy of Finland is gratefully acknowledged.
Copyright information: © 2017 IET. This paper is a postprint of a paper submitted to and accepted for publication in a compilation: Iris and periocular biometric recognition (by Rathgeb and Busch, eds.), and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at the IET Digital Library https://doi.org/10.1049/PBSE005E_ch12.