Analysis of the improvement on textural information in human iris recognition

Eduardo Garea Llano, Mireya S. García-Vázquez, Luis Miguel Zamudio-Fuentes, Juan M. Colores Vargas, Alejandro A. Ramírez-Acosta

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

4 Citas (Scopus)

Resumen

Recent works in the area of biometrics have shown that fusion at segmentation level (FSL) has contributed to the robustness in iris recognition compared with the recognition obtained from a single segmentation. Different segmentation algorithms can produce different iris textural information from the same image. Considering FSL and combining a method for quality evaluation of images, in this paper we present the analysis of the improvement on textural information in human iris images. The images set for the experiments were four international databases, MBGC-V2 (iris video database), CASIA-V3-Interval, CASIA V4 Thousands and UBIRIS v1 (iris image databases). The Equal Error Rate is used as metric to show the improvement of the recognition rates and hence the textural information improvement.

Idioma originalInglés
Título de la publicación alojada7th Latin American Congress on Biomedical Engineering, CLAIB 2016
EditoresJohn Bustamante, Daniel A. Sierra, Isnardo Torres
EditorialSpringer Verlag
Páginas373-376
Número de páginas4
ISBN (versión impresa)9789811040856
DOI
EstadoPublicada - 2017
Evento7th Latin American Congress on Biomedical Engineering, CLAIB 2016 - Bucaramanga, Santander, Colombia
Duración: 26 oct. 201628 oct. 2016

Serie de la publicación

NombreIFMBE Proceedings
Volumen60
ISSN (versión impresa)1680-0737

Conferencia

Conferencia7th Latin American Congress on Biomedical Engineering, CLAIB 2016
País/TerritorioColombia
CiudadBucaramanga, Santander
Período26/10/1628/10/16

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