A New Iris Recognition Approach Based on a Functional Representation

  • Dania Porro-Muñoz
  • Francisco José Silva-Mata
  • Victor Mendiola-Lau
  • Noslen Hernández
  • Isneri Talavera
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8259)


This paper proposes the introduction of annular Zernike polynomials for representing iris images data. This representation offers notables advantages like representing the images on a continuous domain that allows the application of Functional Data Analysis techniques, preserving their original nature. In addition, it provides a significant dimensionality reduction of the data, while it still has a high discriminative power. The proposed approach also deals with the occlusion problems that can be present in this type of images. In order to corroborate the effectiveness of the introduced approach, identification experiments were carried out. Iris international databases were used. Some of them are characterized by the presence of severe occlusion problems. Results have shown high recognition accuracy.


Iris recognition Functional Data Analysis 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Dania Porro-Muñoz
    • 1
  • Francisco José Silva-Mata
    • 1
  • Victor Mendiola-Lau
    • 1
  • Noslen Hernández
    • 1
  • Isneri Talavera
    • 1
  1. 1.Advanced Technologies Application CenterCENATAVCuba

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