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Effect of Tiling in Row Mean of Column Transformed Image as Feature Vector for Iris Recognition with Cosine, Hadamard, Fourier and Sine Transforms

by H. B. Kekre, Sudeep D. Thepade, Donovan Pereira, Kiran Rohra
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 40 - Number 12
Year of Publication: 2012
Authors: H. B. Kekre, Sudeep D. Thepade, Donovan Pereira, Kiran Rohra
10.5120/5015-7344

H. B. Kekre, Sudeep D. Thepade, Donovan Pereira, Kiran Rohra . Effect of Tiling in Row Mean of Column Transformed Image as Feature Vector for Iris Recognition with Cosine, Hadamard, Fourier and Sine Transforms. International Journal of Computer Applications. 40, 12 ( February 2012), 14-18. DOI=10.5120/5015-7344

@article{ 10.5120/5015-7344,
author = { H. B. Kekre, Sudeep D. Thepade, Donovan Pereira, Kiran Rohra },
title = { Effect of Tiling in Row Mean of Column Transformed Image as Feature Vector for Iris Recognition with Cosine, Hadamard, Fourier and Sine Transforms },
journal = { International Journal of Computer Applications },
issue_date = { February 2012 },
volume = { 40 },
number = { 12 },
month = { February },
year = { 2012 },
issn = { 0975-8887 },
pages = { 14-18 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume40/number12/5015-7344/ },
doi = { 10.5120/5015-7344 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:27:52.698883+05:30
%A H. B. Kekre
%A Sudeep D. Thepade
%A Donovan Pereira
%A Kiran Rohra
%T Effect of Tiling in Row Mean of Column Transformed Image as Feature Vector for Iris Recognition with Cosine, Hadamard, Fourier and Sine Transforms
%J International Journal of Computer Applications
%@ 0975-8887
%V 40
%N 12
%P 14-18
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Iris recognition is a biometric authentication method that uses pattern-recognition techniques based on high-resolution images of the irises of an individual's eyes. 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. This paper presents the techniques of iris recognition using image transforms such as Cosine transform, Sine transform, Fourier transform and Hadamard transform. Here iris recognition is done using the image feature vector set extracted as row mean of transformed column iris image. Image tiling is further used for feature extraction for each transform and the performance is compared with the single tile based iris recognition method. Parameters such as False Acceptance Rate and Genuine Acceptance Rate are used to test the performance of the techniques. The results have shown that the proposed Iris recognition methods performs better with increased number of tiles of Iris image up to certain extent of tiling.

References
  1. http://en.wikipedia.org/wiki/Iris_recognition(referred as on 23 December 2011).
  2. Mihran Tuceryan, Anil K Jain, "Chapter 2.1, Texture Analysis", The Handbook of Pattern Recognition and Computer Vision (2nd Edition), by C. H. Chen, L. F. Pau, P. S. P. Wang (eds.), pp. 207-248, World Scientific Publishing Co., 1998.
  3. R.C. Gonzalez, R.E. Woods “Digital Image Processing”, Third Edition, 2008, Upper Saddle River, New Jersey 07458, Pearson Publication.
  4. Dr. H B Kekre, Dr. Sudeep Thepade, Juhi Jain, Naman Agrawal, "IRIS Recognition using Texture Features Extracted from Haarlet Pyramid", International Journal of Computer Applications (0975-8887), Volume 11-No.12, December 2010.
  5. Dr. H.B.Kekre, Sudeep D. Thepade, Varun K. Banura, “Augmentation of Colour Averaging Based Image Retrieval Techniques using Even part of Images and Amalgamation of feature vectors”, International Journal of Engineering Science and Technology (IJEST), Volume 2, Issue 10, (ISSN: 0975-5462).
  6. Dr. H.B.Kekre, Sudeep D. Thepade, Akshay Maloo “Performance Comparison for Face Recognition using PCA, DCT & Walsh Transform of Row Mean and Column Mean”, ICGST International Journal on Graphics, Vision and Image Processing (GVIP), Volume 10, Issue II, Jun.2010, pp.9-18.
  7. Hirata K. and Kato T. “Query by visual example – content-based image retrieval”, In Proc. of Third International Conference on Extending Database Technology, EDBT’92, 1992, pp 56-71.
  8. H B Kekre, Sudeep D. Thepade, Archana A. Athawale, Paulami Shah, “Image Retrieval using Fractional Energy of Row Mean of Column Transformed Image with Six Orthogonal Image Transforms”, International Journal of Soft Computing and Engineering (IJSCE), ISSN: 2231-2307, Volume-1, Issue-4, September 2011.
  9. Dr. H.B.Kekre, Sudeep D. Thepade, “Improving the Performance of Image Retrieval using Partial Coefficients of Transformed Image”, International Journal of Information Retrieval, Serials Publications, Volume 2, Issue 1, 2009, pp. 72-79.
  10. Dr. H.B.Kekre, Sudeep D. Thepade, Akshay Maloo “Performance Comparison of Image Retrieval Using Fractional Coefficients of Transformed Image Using DCT, Walsh, Haar and Kekre’s Transform”, CSC International Journal of Image Processing (IJIP), Volume 4, Issue 2, pp 142-157, Computer Science Journals.
  11. Dr. H B Kekre, Sudeep D. Thepade, Varun K. Banura, “Image Retrieval using Texture Patterns generated from Walsh-Hadamard Transform Matrix and Image Bitmaps”, Springer International Conference on Technology Systems and Management (ICTSM 2011), MPSTME and DJSCOE, Mumbai, 25-27 Feb 2011.
  12. Dr. H B Kekre, Sudeep D. Thepade, Varun K. Banura, “Image Retrieval using Shape Texture Patterns generated from Walsh-Hadamard Transform and Gradient Image Bitmaps”, International Journal of Computer Science and Information Security (IJCSIS), Volume 8, Number 9, 2010.pp.76-82.
  13. http://www.advancedsourcecode.com/irisdatabase.asp for Palacky University iris database.
Index Terms

Computer Science
Information Sciences

Keywords

Iris Recognition Row Mean Image Tiling Image Transforms.

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