Simulating the Influences of Aging and Ocular Disease on Biometric Recognition Performance

  • Halvor Borgen
  • Patrick Bours
  • Stephen D. Wolthusen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5558)

Abstract

Many applications of ocular biometrics require long-term stability, yet only limited data on the effects of disease and aging on the error rates of ocular biometrics is currently available. Based on pathologies simulated using image manipulation validated by opthalmology and optometry specialists, the present paper reports on the effects that selected common ocular diseases and age-related pathologies have on the recognition performance of two widely used iris and retina recognition algorithms, finding the algorithms to be robust against many even highly visible pathologies, permitting acceptable re-enrolment intervals for most disease progressions.

Keywords

Diabetic Retinopathy Recognition Performance Iris Image Trabecular Meshwork Ocular Disease 
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 2009

Authors and Affiliations

  • Halvor Borgen
    • 1
  • Patrick Bours
    • 1
  • Stephen D. Wolthusen
    • 1
    • 2
  1. 1.Norwegian Information Security LaboratoryGjøvik University CollegeGjøvikNorway
  2. 2.Information Security Group, Department of Mathematics, Royal HollowayUniversity of LondonEghamUnited Kingdom

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