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Reseach Article

Iris Feature Extraction and Matching by using Wavelet Decomposition and Hamming Distance

by A. T. Gaikwad, Mouad M. H. Ali
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 158 - Number 4
Year of Publication: 2017
Authors: A. T. Gaikwad, Mouad M. H. Ali
10.5120/ijca2017912793

A. T. Gaikwad, Mouad M. H. Ali . Iris Feature Extraction and Matching by using Wavelet Decomposition and Hamming Distance. International Journal of Computer Applications. 158, 4 ( Jan 2017), 43-47. DOI=10.5120/ijca2017912793

@article{ 10.5120/ijca2017912793,
author = { A. T. Gaikwad, Mouad M. H. Ali },
title = { Iris Feature Extraction and Matching by using Wavelet Decomposition and Hamming Distance },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2017 },
volume = { 158 },
number = { 4 },
month = { Jan },
year = { 2017 },
issn = { 0975-8887 },
pages = { 43-47 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume158/number4/26899-2017912793/ },
doi = { 10.5120/ijca2017912793 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:03:58.102372+05:30
%A A. T. Gaikwad
%A Mouad M. H. Ali
%T Iris Feature Extraction and Matching by using Wavelet Decomposition and Hamming Distance
%J International Journal of Computer Applications
%@ 0975-8887
%V 158
%N 4
%P 43-47
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The security system nowadays using biometrics traits is a confident and reliable of some biometrics system. The reason of that is uniqueness and permanents of those traits. In this paper the Iris recognition system is covering step by steps started namely Acquisition stage ,preprocessing which includes the segmentation, pupil boundary detect and Normalization the next stage is feature extraction which used the wavelet decomposition methods , the finally the matching stage is perform with help of hamming distance measure, then the results are show in different dataset size of training and testing sets finally the evaluation of the system conducted based on FAR , FRR and EER of the system.

References
  1. Anil K. jain, Arun A.Ross, Karthik Nanda kumar, 2011, "introduction to biometrics", Springer Sciences + Business Media, LLC, 233 Spring Street, New York ,NY 10013, USA
  2. Biometrics identification: http://www.tml.tkk.fi/Opinnot/Tik-110.501/1998/papers/12biometric/biometric.html
  3. Iris introduction available on this web: http://en.irisking.com/html/47/product40
  4. J. G. Daugman, 1993 “high confidence visual recognition of persons by a test of statistical independence”, IEEE transactions on pattern analysis and machine intelligence, 15 (11) ,1148 1160
  5. L. Masek, 2003 , “Recognition of Human Iris Patterns for Biometric Identification‖” , M.S. Dissertation, the University of Western Australia
  6. P. Verma, M. Dubey, P. Verma and S. Basu, 2012, “Duaghman’s algorithm method for iris recognition- a biometric approach”,IJETAE international journal of emerging technology and advanced engineering, ISSN 2250-2459, vol. 2 , issue 6
  7. E. Krichen, M.A. Mellakh, S. G. Salicetti and B. Dorizzi, 2004, “iris identification using wavelet packets” IEEE proceedings of the 17th international conference on pattern recognition (ICPR04), vol. no 04
  8. Abikoye Oluwakemi C., Sadiku, J. S., Adewole Kayode S., and Jimoh Rasheed G, 2014,”Iris Feature Extraction for Personal Identification using Fast Wavelet Transform (FWT)”, International Journal of Applied Information Systems (IJAIS), ISSN : 2249-0868, Volume 6– No. 9.
  9. Yuqing He, Guangqin Feng, Yushi Hou, Li Li and Evangelia Micheli-Tzanakou, 2011 ,“Iris feature extraction method based on LBP and chunked encoding ”, Seventh IEEE International Conference on Natural Computation 2011, 978-1-4244-9953-3
  10. J. Daugman, 2004, “How Iris Recognition Works,” IEEE Trans.on Circuits and Systems for Video Technology, vol. 11, pp. 21-30.
  11. Wildes. R: 1997, “Iris recognition: an emerging biometric technology” . In: Proceedings of the IEEE, Vol. 85, No. 9.
  12. Boles W. W, Bolash. B: 1998, ” A human identification technique using images of the iris and wavelet transform” . In: IEEE transactions on signal processing, Vol. 46, issue 4,1185-1188.
  13. Jain A, Bolle R and Pankanti S: 1999, “ Biometrics: Personal Identification in a Networked Society” . MA: Kluwer, Norwell,
  14. Daugman, J.“How Iris Recognition Works”,available at http://www.ncits.org/tc_home/m1htm/docs/m1020044.pdf.
  15. Daugman, J., 1993. “High Confidence Visual Recognition of Persons by a Test of Statistical Independence ,”IEEE transactions on pattern analysis and machine intelligence, vol. 15, no.11,pp. 1148-1161.
  16. M. M. H. Ali, V. H. Mahale, P. Yannawar and A. T. Gaikwad, 2016, "Fingerprint Recognition for Person Identification and Verification Based on Minutiae Matching," 2016 IEEE 6th International Conference on Advanced Computing (IACC), Bhimavaram, pp. 332-339
Index Terms

Computer Science
Information Sciences

Keywords

Iris Recognition preprocessing Feature Extraction Matching Wavelet Decomposition Hamming Distance.