Encyclopedia of Biometrics

2009 Edition
| Editors: Stan Z. Li, Anil Jain

Iris Recognition Using Correlation Filters

  • Yung-hui Li
  • Marios Savvides
  • Jason Thornton
  • B. V. K. Vijaya Kumar
Reference work entry
DOI: https://doi.org/10.1007/978-0-387-73003-5_178



Algorithms for iris recognition usually consist of applying feature extraction on raw iris pattern, then matching against features. However, two important techniques in machine learning and pattern recognition, namely probabilistic graphical model, and advanced correlation filters, have not been used for iris recognition. By using probabilistic graphical models for iris texture deformation, with the observation being the correlation output derived from applying correlation filters to local iris regions, problems of iris pattern local deformations and occlusions can be handled and recognition performance can be improved over that of the conventional iris recognition algorithms.


In the past two decades, iris recognition has emerged as one of the most promising modalities for biometric recognition. Many algorithms have been proposed to improve the recognition performance of iris recognition....
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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Yung-hui Li
    • 1
  • Marios Savvides
    • 2
  • Jason Thornton
    • 2
  • B. V. K. Vijaya Kumar
    • 2
  1. 1.Language Technology InstituteCarnegie Mellon UniversityPittsburghUSA
  2. 2.Department of Electrical and Computer EngineeringCarnegie Mellon UniversityPittsburghUSA