Iris image evaluation for non-cooperative biometric iris recognition system

Juan M. Colores, Mireya García-Vázquez, Alejandro Ramírez-Acosta, Héctor Pérez-Meana

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

During video acquisition of an automatic non-cooperative biometric iris recognition system, not all the iris images obtained from the video sequence are suitable for recognition. Hence, it is important to acquire high quality iris images and quickly identify them in order to eliminate the poor quality ones (mostly defocused images) before the subsequent processing. In this paper, we present the results of a comparative analysis of four methods for iris image quality assessment to select clear images in the video sequence. The goal is to provide a solid analytic ground to underscore the strengths and weaknesses of the most widely implemented methods for iris image quality assessment. The methods are compared based on their robustness to different types of iris images and the computational effort they require. The experiments with the built database (100 videos from MBGC v2) demonstrate that the best performance scores are generated by the kernel proposed by Kang & Park. The FAR and FRR obtained are 1.6% and 2.3% respectively. © 2011 Springer-Verlag.
Original languageAmerican English
Title of host publicationIris image evaluation for non-cooperative biometric iris recognition system
Pages499-509
Number of pages448
ISBN (Electronic)9783642253294
DOIs
StatePublished - 6 Dec 2011
Externally publishedYes
EventLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) -
Duration: 1 Jan 2014 → …

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7095 LNAI
ISSN (Print)0302-9743

Conference

ConferenceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Period1/01/14 → …

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Colores, J. M., García-Vázquez, M., Ramírez-Acosta, A., & Pérez-Meana, H. (2011). Iris image evaluation for non-cooperative biometric iris recognition system. In Iris image evaluation for non-cooperative biometric iris recognition system (pp. 499-509). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7095 LNAI). https://doi.org/10.1007/978-3-642-25330-0_44