Iris image evaluation for non-cooperative biometric iris recognition system

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

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferencia

10 Citas (Scopus)

Resumen

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.
Idioma originalInglés estadounidense
Título de la publicación alojadaIris image evaluation for non-cooperative biometric iris recognition system
Páginas499-509
Número de páginas448
ISBN (versión digital)9783642253294
DOI
EstadoPublicada - 6 dic 2011
Publicado de forma externa
EventoLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) -
Duración: 1 ene 2014 → …

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen7095 LNAI
ISSN (versión impresa)0302-9743

Conferencia

ConferenciaLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Período1/01/14 → …

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  • Citar esto

    Colores, J. M., García-Vázquez, M., Ramírez-Acosta, A., & Pérez-Meana, H. (2011). Iris image evaluation for non-cooperative biometric iris recognition system. En 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