Iris Recognition with Support Vector Machines

  • Kaushik Roy
  • Prabir Bhattacharya
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3832)


We propose an iris recognition system for the identification of persons using support vector machines. Canny’s edge detection and the Hough transform are used to find the iris/pupil boundary and a simple thresholding method is employed for eyelash detection. The Gabor wavelet technique is deployed in order to extract the deterministic features in the transformed iris of a person in the form of template. The extracted iris features are fed into a support vector machine (SVM) for classification. Our results indicate that the performance of SVM as a classifier is far better than the performance of a classifier based on the artificial neural network.


Support Vector Machine Iris Region Iris Image Radial Basis Function Kernel False Reject Rate 
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 2005

Authors and Affiliations

  • Kaushik Roy
    • 1
  • Prabir Bhattacharya
    • 1
  1. 1.Concordia Institute for Information System EngineeringConcordia UniversityMontrealCanada

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