Iris Segmentation and Recognition Using 2D Log-Gabor Filters

  • Carlos A. C. M. Bastos
  • Tsang Ing Ren
  • George D. C. Cavalcanti
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7435)

Abstract

This paper describes an analysis on the parameters used to construct 2D log-Gabor filters to encode iris patterns. An iris recognition system, composed by segmentation, normalization, encoding and matching is also described. The segmentation module combines the Pulling & Pushing and Active Contour Model and the Circular Hough Transform to find the inner and the outter boundaries of the iris. The experiments were performed using the CASIA v.1 iris database and the results are analyzed using ROC curves. They showed that 2D log-Gabor filters are also an effective alternative to encode the features present on iris patterns.

Keywords

Equal Error Rate Active Contour Model False Acceptance Rate Iris Recognition Pupil Center 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Carlos A. C. M. Bastos
    • 1
  • Tsang Ing Ren
    • 1
  • George D. C. Cavalcanti
    • 1
  1. 1.Center of InformaticsFederal University of Pernambuco – CIn/UFPERecifeBrazil

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