Video Images Fusion to Improve Iris Recognition Accuracy in Unconstrained Environments

  • Juan M. Colores-Vargas
  • Mireya García-Vázquez
  • Alejandro Ramírez-Acosta
  • Héctor Pérez-Meana
  • Mariko Nakano-Miyatake
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7914)

Abstract

To date, research on the iris recognition systems are focused on the optimization and proposals of new stages for uncontrolled environment systems to improve the recognition rate levels. In this paper we propose to exploit the biometric information from video-iris, creating a fusioned normalized template through an image fusion technique. Indeed, this method merges the biometric features of a group of video images getting an enhanced image which therefore improves the recognition rates iris, in terms of Hamming distance, in an uncontrolled environment system. We analyzed seven different methods based on pixel-level and multi-resolution fusion techniques on a subset of images from the MBGC.v2 database. The experimental results show that the PCA method presents the best performance to improve recognition values according to the Hamming distances in 83% of the experiments.

Keywords

Fusion Iris MBGC PCA Recognition 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Juan M. Colores-Vargas
    • 1
  • Mireya García-Vázquez
    • 1
  • Alejandro Ramírez-Acosta
    • 2
  • Héctor Pérez-Meana
    • 3
  • Mariko Nakano-Miyatake
    • 3
  1. 1.Instituto Politécnico NacionalCITEDITijuanaMéxico
  2. 2.MIRAL R&DImperial BeachUSA
  3. 3.ESIMEInstituto Politécnico NacionalDF. MéxicoMexico

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