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Iris Recognition

Published on April 2012 by Shirke Swati D, Shirke Suvarna D, Gupta Deepak
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Emerging Trends in Computer Science and Information Technology (ETCSIT2012)
Foundation of Computer Science USA
ETCSIT - Number 1
April 2012
Authors: Shirke Swati D, Shirke Suvarna D, Gupta Deepak
670d2df4-637b-48df-9d33-1baab588355c

Shirke Swati D, Shirke Suvarna D, Gupta Deepak . Iris Recognition. Emerging Trends in Computer Science and Information Technology (ETCSIT2012). ETCSIT, 1 (April 2012), 20-23.

@article{
author = { Shirke Swati D, Shirke Suvarna D, Gupta Deepak },
title = { Iris Recognition },
journal = { Emerging Trends in Computer Science and Information Technology (ETCSIT2012) },
issue_date = { April 2012 },
volume = { ETCSIT },
number = { 1 },
month = { April },
year = { 2012 },
issn = 0975-8887,
pages = { 20-23 },
numpages = 4,
url = { /proceedings/etcsit/number1/5963-1006/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 Emerging Trends in Computer Science and Information Technology (ETCSIT2012)
%A Shirke Swati D
%A Shirke Suvarna D
%A Gupta Deepak
%T Iris Recognition
%J Emerging Trends in Computer Science and Information Technology (ETCSIT2012)
%@ 0975-8887
%V ETCSIT
%N 1
%P 20-23
%D 2012
%I International Journal of Computer Applications
Abstract

Algorithms developed for recognizing persons by their iris patterns have now been tested in many field and laboratory trials, producing no false matches in several million comparison tests [3]. We present an efficient Iris Code classifier, built from phase features which use Gabor wavelets bandwidths [1]. The final iris classifier consists of a weighted contribution of weak classifiers. Based on the Levenshtein distance between phase vectors of the respective iris images [4]. Our experiments show that the Levenshtein distance has better discrimination in comparing Iris Codes than the Hamming distance [1] IRIS Recognition is used of Identification, Authentication,and Scanning . IRIS Is a Muscle which is placed in between Pupil and Sclera[2].

References
  1. . Ioan Climent,Juan Diego Blanco, Roberto A Hexcel(Approximate String matching for Iris recognition by means of boosted Gabor Wavelet" IEEE Trans on Systems,2010 23rd SIBGRAPI
  2. J. L. Wayman, A. K. Jain, D. Maltoni, and D. M. (Eds. ),Biometric Systems. Springer-Verlag, 2005, isbn 978-1-85233-596-0. 46
  3. . J. G. Daugman, "High confidence visual recognition of persons by a test of statistical independence," IEEE Trans on Pattern Analysis and Machine Intelligence, vol. 15, no. 11,pp. 1148–1161, 1993.
  4. . "New methods in iris recognition," IEEE Trans on Systems, Man and Cybernetics, part B: Cybernetics, vol. 37,
  5. . R. P. Wildes, "Iris recognition: An emerging biometric technology,"Proc of the IEEE, vol. 85, no. 9, pp. 1348–1363,Sep. 1997.
  6. . W. W. Boles and B. Boashash, "A human identification technique using images of the iris and wavelet transform," IEEE Trans on Signal Processing, vol. 46, no. 4, pp. 1185–1188, Apr. 1998.
  7. L. Ma, Y. Wang, and T. Tan, "Iris recognition using circular symmetric filters," in Int Conf on Pattern Recognition (ICPR'02), vol. 2, 2002, pp. 414–417.
  8. . L. Ma, T. Tan, Y. Wang, and D. Zhang, "Efficient iris recognition by characterizing key local variations," IEEE Trans on Image Processing, vol. 13, no. 6, pp. 739–750, Jun. 2004.
Index Terms

Computer Science
Information Sciences

Keywords

Iris Recognition Biometrics Levenstein Distance Gaborwavelet