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A Theoretical Model for Describing Iris Dynamics

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Handbook of Iris Recognition

Part of the book series: Advances in Computer Vision and Pattern Recognition ((ACVPR))

Abstract

We present a theoretical approach using what we know about tissue dynamics to explore the nonlinear dynamics of iris deformation. Current iris recognition algorithms assume a simple transformation to approximate the deformation of the iris tissue. Furthermore, current research work on iris deformation does not take into account the mechanical properties of the iris tissue nor the cause of deformation from the iris muscle activity. By looking at the tissue dynamics, we are able to gain a more comprehensive understanding of this deformation process. The results of this research work can potentially be leveraged into existing iris recognition systems.

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Acknowledgments

This material is based upon work supported by the U.S. Department of Homeland Security under Grant Award Number 2007-ST-104-000006. The views and conclusions contained in this document are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of the U.S. Department of Homeland Security. Arun Ross was supported by US National Science Foundation CAREER Grant No. IIS 0642554

Author information

Authors and Affiliations

  1. West Virginia University, Morgantown, WV, USA

    Antwan Clark

  2. Climate Central, Princeton, NJ, USA

    Scott Kulp

  3. Rensselaer Polytechnic Institute, Troy, NY, USA

    Isom Herron

  4. Integrated Pattern Recognition and Biometrics Lab (i-PRoBe), Michigan State University, East Lansing, MI, USA

    Arun A. Ross

Authors
  1. Antwan Clark
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  2. Scott Kulp
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  3. Isom Herron
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  4. Arun A. Ross
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Corresponding authors

Correspondence to Scott Kulp , Isom Herron or Arun A. Ross .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, Indiana, USA

    Kevin W. Bowyer

  2. Noblis, Inc., Washington, District of Columbia, USA

    Mark J. Burge

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© 2016 Springer-Verlag London

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Clark, A., Kulp, S., Herron, I., Ross, A.A. (2016). A Theoretical Model for Describing Iris Dynamics. In: Bowyer, K., Burge, M. (eds) Handbook of Iris Recognition. Advances in Computer Vision and Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-4471-6784-6_18

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  • DOI: https://doi.org/10.1007/978-1-4471-6784-6_18

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-6782-2

  • Online ISBN: 978-1-4471-6784-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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