Performance Analysis of Iris Recognition System

  • Ruqaiya Khanam
  • Zohreen Haseen
  • Nighat Rahman
  • Jugendra Singh
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 847)


A biometric system offers automatic identification of an individual based on a unique feature or characteristic possessed by the individual. Iris recognition is regarded as the most reliable and accurate biometric identification system available. Although iris identification system is based on pattern recognition technique but due to poor iris boundary detection and high computational time in previous work, we used neural network and discriminant machine learning technique to obtained high accuracy. In this work, we implement neural network and discriminant analysis of machine learning method for iris recognition in iris images to implement in day-to-day life, using MATLAB 2016a. The emphasis will be only on the software for performing recognition and not hardware for capturing an eye image. The proposed method gives better recognition rate than SVM technique with less computational complexity. Neural network and discriminant methods are used for matching and finding recognition accuracy. Thus, the accuracy obtained from neural network is 94.44%, whereas from discriminant analysis the accuracy obtained is 99.99%.


Iris recognition Neural network Machine learning 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Ruqaiya Khanam
    • 1
  • Zohreen Haseen
    • 1
  • Nighat Rahman
    • 1
  • Jugendra Singh
    • 1
  1. 1.Galgotias UniversityGreater NoidaIndia

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