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Reseach Article

Article:IRIS Recognition using Texture Features Extracted from Haarlet Pyramid

by Dr.H.B.Kekre, Sudeep D. Thepade, Juhi Jain, Naman Agrawal
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 11 - Number 12
Year of Publication: 2010
Authors: Dr.H.B.Kekre, Sudeep D. Thepade, Juhi Jain, Naman Agrawal
10.5120/1638-2202

Dr.H.B.Kekre, Sudeep D. Thepade, Juhi Jain, Naman Agrawal . Article:IRIS Recognition using Texture Features Extracted from Haarlet Pyramid. International Journal of Computer Applications. 11, 12 ( December 2010), 1-5. DOI=10.5120/1638-2202

@article{ 10.5120/1638-2202,
author = { Dr.H.B.Kekre, Sudeep D. Thepade, Juhi Jain, Naman Agrawal },
title = { Article:IRIS Recognition using Texture Features Extracted from Haarlet Pyramid },
journal = { International Journal of Computer Applications },
issue_date = { December 2010 },
volume = { 11 },
number = { 12 },
month = { December },
year = { 2010 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume11/number12/1638-2202/ },
doi = { 10.5120/1638-2202 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:00:21.530517+05:30
%A Dr.H.B.Kekre
%A Sudeep D. Thepade
%A Juhi Jain
%A Naman Agrawal
%T Article:IRIS Recognition using Texture Features Extracted from Haarlet Pyramid
%J International Journal of Computer Applications
%@ 0975-8887
%V 11
%N 12
%P 1-5
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Iris recognition has been a fast growing, challenging and interesting area in real-time applications. A large number of iris recognition algorithms have been developed for decades. The paper presents novel Haarlet Pyramid based iris recognition technique. Here iris recognition is done using the image feature set extracted from Haar Wavelets at various levels of decomposition. Analysis was performed of the proposed method, consisting of the False Acceptance Rate and the Genuine Acceptance Rate. The proposed technique is tested on an iris image database having 384 images. The results show that Haarlets level-5 outperforms other Haarlets, because the higher level Haarlets are giving very fine texture features while the lower level Haarlets are representing very coarse texture features which are less useful for discrimination of images in iris recognition.

References
  1. Developed by Dr. Libor Spacek. Available Online at: http://cswww.essex.ac.uk/mv/otherprojects.html. [last referred on 10 Nov 2010]
  2. H.B.Kekre, Sudeep D. Thepade, “Image Retrieval using Color-Texture Features Extracted from Haarlet Pyramid”, ICGST International Journal on Graphics, Vision and Image Processing (GVIP), Volume 10, Issue I, Feb.2010, pp.9-18, Available online www.icgst.com/gvip/Volume10/Issue1/P1150938876.html
  3. H.B.Kekre, Sudeep D. Thepade, “Creating the Color Panoramic View using Medley of Grayscale and Color Partial Images ”, WASET International Journal of Electrical, Computer and System Engineering (IJECSE), Volume 2, No. 3, Summer 2008. Available online at www.waset.org/ijecse/v2/v2-3-26.pdf.
  4. Stian Edvardsen, “Classification of Images using color, CBIR Distance Measures and Genetic Programming”, Ph.D. Thesis, Master of science in Informatics, Norwegian university of science and Technology, Department of computer and Information science, June 2006.
  5. H.B.Kekre, Tanuja Sarode, Sudeep D. Thepade, “DCT Applied to Row Mean and Column Vectors in Fingerprint Identification”, In Proceedings of International Conference on Computer Networks and Security (ICCNS), 27-28 Sept. 2008, VIT, Pune.
  6. Zhibin Pan, Kotani K., Ohmi T., “Enhanced fast encoding method for vector quantization by finding an optimally-ordered Walsh transform kernel”, ICIP 2005, IEEE International Conference, Volume 1, pp I - 573-6, Sept. 2005.
  7. H.B.Kekre, Sudeep D. Thepade, “Improving ‘Color to Gray and Back’ using Kekre’s LUV Color Space”, IEEE International Advanced Computing Conference 2009 (IACC’09), Thapar University, Patiala, INDIA, 6-7 March 2009. Is uploaded and available online at IEEE Xplore.
  8. H.B.Kekre, Sudeep D. Thepade, “Image Blending in Vista Creation using Kekre's LUV Color Space”, SPIT-IEEE Colloquium and International Conference, Sardar Patel Institute of Technology, Andheri, Mumbai, 04-05 Feb 2008.
  9. H.B.Kekre, Sudeep D. Thepade, “Color Traits Transfer to Grayscale Images”, In Proc.of IEEE First International Conference on Emerging Trends in Engg. & Technology, (ICETET-08), G.H.Raisoni COE, Nagpur, INDIA. Uploaded on online IEEE Xplore.
  10. http://www.webopedia.com/TERM/F/false_rejection.html [last referred on 10 Nov 2010]
  11. http://www.webopedia.com/TERM/F/genuine_acceptance.html [last referred on 10 Nov 2010]
  12. K.-C. Liang and C. C. Kuo, "WaveGuide: A Joint Wavelet-Based Image Representation and Description System," IEEE Trans. on ImageProcessing, vol. 8, no. 11, pp.1619-1629, 1999
  13. Haar, Alfred, “Zur Theorie der orthogonalen Funktionensysteme”. (German), Mathematische Annalen, volume 69, No. 3, 1910, pp. 331–371.
  14. Charles K. Chui, “An Introduction to Wavelets”, Academic Press, 1992, San Diego, ISBN 0585470901.
  15. www.wisegeek.com/what-is-iris-recognition-technology.htm
  16. A. Basit, M. Y. Javed, M. A. Anjum, "Efficient Iris Recognition Method for Human Identification." Uploaded on online IEEE Xplore.
  17. Christel-loïc TISSE, Lionel MARTIN, Lionel TORRES, Michel ROBERT, "Person identification technique using human iris recognition." Uploaded on online IEEE Xplore.
  18. "http://www.advancedsourcecode.com/irisdatabase.asp" for Palacky University iris database.
Index Terms

Computer Science
Information Sciences

Keywords

Iris recognition Haarlet Pyramid Haarlet Levels False Acceptance Rate Genuine Acceptance Rate