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Ordinal entropy-based novel personal identification using colour channels of visible-light iris image

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Abstract

This paper proposes an iris recognition system for use with visible-light iris images employing the nonlinear analysis method of dispersion entropy (DE). The difference in the pattern of iris between different individuals is identified by fusing correlation between sets of the DE values of rows and columns of each RGB channel. The colour iris images from the popular iris database UPOL are used in experimental analysis. The results show that the differential identification of iris images can be effectively performed by this proposed method.

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Availability of data and materials

The UPOL iris dataset analysed in this study is obtained from the iris database provided by Michal Dobeš and Libor Machala, Iris Database, http://phoenix.inf.upol.cz/iris/

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Acknowledgements

The authors would like to thank and acknowledge the valuable inputs provided to us to improve the manuscript. One of the authors Bindu M Krishna would like to thank Dr. M. Gopalakrishna Pillai, Director, STIC, CUSAT, for the extensive support and encouragement provided for doing the research work.

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No funds, grants, or other support was received.

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Authors and Affiliations

  1. Department of Computer Engineering, Cochin University of Science and Technology, Kochi, India

    S. Sheena & Sheena Mathew

  2. Sophisticated Test and Instrumentation Centre, Cochin University of Science and Technology, Kochi, India

    Bindu M. Krishna

Authors
  1. S. Sheena
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  2. Sheena Mathew
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  3. Bindu M. Krishna
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All authors wrote and reviewed the whole manuscript.

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Correspondence to Bindu M. Krishna.

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Sheena, S., Mathew, S. & Krishna, B.M. Ordinal entropy-based novel personal identification using colour channels of visible-light iris image. SIViP 17, 3893–3901 (2023). https://doi.org/10.1007/s11760-023-02618-8

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