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Comparative Study on Biometric Iris Recognition based on Hamming Distance and Multi Block Local Binary Pattern


  • Department of Computer Science, A.V.V.M. Sri Pushpam College, Poondi-613503, India
  • Department of Software Engineering, Periyar Maniammai University, Vallam-613403, India


Personal identification based on biometric is most essential to ensure security. Recognition based on iris unique texture is a reliable, simple and fast. The abundant as well as unique patterns of iris are extracted. Matrix format template is generated that contains 4800 elements for each iris. Multi block local binary pattern, hamming distance and support vector machine performs matching based on the template’s unique features of iris. The experimental results of this proposed work illustrate a better performance. The popular CASIA (Chinese Academy of Sciences – Institute of Automation) iris database with hundred users’ eye image samples are experimented to prove, that the multi block local binary pattern is comparatively better with minimal true rejection rate.


Hamming Distance, Iris Preprocessing, Iris Template, Multi Block Local Binary Pattern

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