Wavefront Coding for Iris Recognition

Authors

  • R. Subha  Research Scholar, Mother Teresa Women's University, Kodaikanal, Tamil Nadu, India
  • Dr. M.Pushpa Rani  Professor & Head, Department of Computer Science, Mother Theresa Women's University, Tamil Nadu, India

Keywords:

Randomness, Entropy Density, Illumination.

Abstract

Iris recognition can offer high-accuracy person identification, particularly when the acquired iris image is well focused. Iris identification is one of the most eye-catching approaches due to its nature of randomness, texture stability over a life time, high entropy density and non-invasive acquisition. While the performance of iris identification on high quality image is well investigated, not too many studies addressed that how iris recognition performs subject to non-ideal image data, especially when the data is acquired in challenging conditions, such as long working distance, dynamical movement of subjects, uncontrolled illumination conditions and so on. This presents the overview of several of Wave front Coding for Iris Recognition.

References

  1. http://wavefrontbiometric.com/
  2. "Extended-Depth-of-Field Iris Recognition Using Unrestored Wavefront-Coded Imagery" Vishnu Naresh Boddeti, Student Member, IEEE, and B. V. K. Vijaya Kumar,IEEE transactions on systems, man, and cybernetics—part a: systems and humans, vol. 40, no. 3, may2010.
  3. "Performance Evaluation of Wavefront Coding for Iris Recognition", Vishnu Naresh Boddeti and B.V.K. Vijaya Kumar.
  4. "Biometric iris image acquisition system with wavefront coding technology", Sheng-Hsun Hsieha, Hsi-Wen Yanga, Shao-Hung     Huanga, Yung-Hui Lib and Chung-Hao Tiena
  5. A. K. Jain, A. Ross, and S. Prabhakar, "An Introduction to Biometric Recognition," IEEE Transactions on Circuits and System for Video Technology, 14(1), 4-20 (2004).
  6. J. Daugman, "The importance of being random: statistical principles of iris recognition," Pattern Recognition 36, 279-291 (2003)
  7. J. Daugman, "How iris recognition works," IEEE Transaction on Circuits and Systems for Video Technology 14(1), 21-30 (2004)
  8. E. R. Dowski, and W. T. Cathey, "Extended depth of field through wavefront coding," Applied Optics 34(11), 1859-1866 (1995)
  9. S. Sherif, E. Dowski, and W. Cathey, "A logarithmic phase filter to extend the depth of field of incoherent hybrid imaging systems," Algorithms and Systems for Optical Information Processing V, 272-279 (2001)
  10. K. Kubala, E. Dowski, J. Kobus, and R. Brown, "Design and optimization of aberration and error invariant space telescope systems," Proceeding of the SPIE 5542, 54-65 (2004)
  11. K. Nguyen, C. Fookes, S. Sridharan, S. Denman, "Quality-Driven Super-Resolution for Less Constrained Iris Recognition at a Distance and on the Move," IEEE Transactions on Information Forensics and Security 6(4), 1248-1258(2011)
  12. J. R. Matey, O. Naroditsky, K. Hanna, R. Kolczynski, D. J. Lolacono, S. Mangru, M. Tinker, T. M. Zappia, and W. Y. Y. Zhao, "Iris on the Move: Acquisition of Images for Iris Recognition in Less Constrained Environments," Proceedings of the IEEE 94(11), 1936-1947 (2006)
  13. J. Daugman, "High confidence visual recognition of persons by a test of statistical independence," IEEE Transaction on Pattern     Analysis and Machine Intelligence 15(11), 1148-1161, (1993)

Downloads

Published

2017-10-31

Issue

Section

Research Articles

How to Cite

[1]
R. Subha, Dr. M.Pushpa Rani, " Wavefront Coding for Iris Recognition, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 5, pp.89-92, September-October-2017.