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Robust Iris Templates for Efficient Person Identification

  • Abhishek Gangwar
  • Akanksha Joshi
  • Renu Sharma
  • Zia Saquib
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 166)

Abstract

Iris recognition is seen as a highly reliable biometric technology. The performance of iris recognition is severely impacted when encountering irises captured in realistic conditions. The selection of the features subset and the classification is an important issue for iris biometrics. In this paper we propose new methods for feature extraction and template creation during enrollment to improve the performance of iris recognition systems. The experiments are based on storing i) multiple templates (template group) for a user ii) Single template by taking average mean of multiple templates iii) Single template calculated from multiple templates using Direct Linear Discriminant Analysis (DLDA). We used CASIA Iris Interval database for our experiments. Experiments report significant improvement in the performance of iris recognition.

Keywords

Feature Extraction Biometric Identification Wavelet Transform template creation 

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Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  • Abhishek Gangwar
    • 1
  • Akanksha Joshi
    • 1
  • Renu Sharma
    • 1
  • Zia Saquib
    • 1
  1. 1.Center for Development of Advanced ComputingMumbaiIndia

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