CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

IRIS Classification based on Fractal Dimension Box Counting Method

by Pravin S.patil
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 112 - Number 11
Year of Publication: 2015
Authors: Pravin S.patil
10.5120/19712-1477

Pravin S.patil . IRIS Classification based on Fractal Dimension Box Counting Method. International Journal of Computer Applications. 112, 11 ( February 2015), 21-27. DOI=10.5120/19712-1477

@article{ 10.5120/19712-1477,
author = { Pravin S.patil },
title = { IRIS Classification based on Fractal Dimension Box Counting Method },
journal = { International Journal of Computer Applications },
issue_date = { February 2015 },
volume = { 112 },
number = { 11 },
month = { February },
year = { 2015 },
issn = { 0975-8887 },
pages = { 21-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume112/number11/19712-1477/ },
doi = { 10.5120/19712-1477 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:49:13.653460+05:30
%A Pravin S.patil
%T IRIS Classification based on Fractal Dimension Box Counting Method
%J International Journal of Computer Applications
%@ 0975-8887
%V 112
%N 11
%P 21-27
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Among many biometrics approaches, iris recognition is known for its high reliability, but as databases grow ever larger, an approach is needed that can reduce matching time. This can be easily achieved by using iris classification This paper presents fractal dimension box counting method for classifying the iris images into four categories according to texture pattern. Initially eye image is localized by using random circular contour method than a preprocessed flat bed iris image of 256 64 size is generated, which is further divided into sixteen regions. Eight regions are drawn from the middle part of the iris image, The remaining eight regions are drawn from the bottom part of the iris image. From these sixteen regions sixteen 32×32 image blocks are generated. To calculate the fractal dimensions of these image blocks box counting method is used. This produces sixteen fractal dimensions. The mean values of the fractal dimensions of the two groups are taken as the upper and lower group fractal dimensions; respectively The double threshold algorithm uses to classify the iris into the four categories. Peformance of the implemented algorithms have been evaluated using confusion matrix and experimental results are reported. The classification method has been tested and evaluated on CASIA V1 iris database.

References
  1. J. Daugman (1994), "Biometric Personal identification System based on iris analysis", US patent no. 529160.
  2. J. Daugman,(2007), "New methods in Iris Recognition," IEEE transactions on systems, man and cybernetics-part B:Cybernetics 37(5), 1167-1175
  3. Z. Sun (2014), "Iris Image classification Based on Hierachical Visual Codebook" ," IEEE Transactions on pattern analysis and machine intelligence. 36 (. 6), 1120-1133.
  4. E. Srinivasa Reddy and I. Ramesh Babu,(2007) "Biometric template classification: A case study in iris textures," ICGST-BIME Journal, vol. 7, issues 1, pp 17-22
  5. J. Daugman (2003), "Demodulation by Complex valued wavelets for stochastic pattern recognition", International Journal of Wavelets, Multiresolution and Information Processing, 1(1), 1-17
  6. P. Perona (1998) " Orientation Diffusion",IEEE Transction on Image Processing,vol. 7,pp. 457-467
  7. M. Tuceryan and A. Jain. Texture analysis. In C. H. Chen, L. F. Pau, and P. S. P. Wang,(1993) "Handbook Pattern Recognition and Computer Vision" World Scientific Publishing,pp 235-276
  8. Z. Sun,Y. Wang,T. Tan,J. Cui (2004) " Robust Direction Estimation of Gradient Vector Field for Iris Recognition" IEEE International Conference
  9. A. P. Pentland (1984) " Fractal-based description of natural scenes," IEEE Transactions on Pattern Analysis and Machine Intelligence 6 pp 661–674.
  10. B. B. Mandelbrot (1982) "The Fractal Geometry of Nature, Freeman, San Francisco," CA,
  11. B. B. Chaudhuri, N Sarker (1995) " Texture segmentation using fractal dimension," IEEE Transactions on Pattern Analysis and Machine Intelligence 17, 72–77
  12. Pravin S. Patil (2012) "Iris Recognition Based on Gaussian-Hermite Moments" International Journal Computer Science and Engineering. (IJCSE),. 4(11) 1794-1803
  13. Pravin S. Patil, Satish R. Kolhe (2010) "Robust Porsonal Identification using Iris" Ascent Journals, International Journal for Engineering Research and Industial Application. (IJERIA) 3(4) 165-177
  14. W. Kong, D. Zhang (2001) "Accurate iris segmentation based on novel reflection and eyelashes detection model," Proceeding of International symposium on intelligent multimedia, video and speech processing Hong Kong
  15. J. Daugman (2006) Probing the uniqueness and randomness of iriscodes: Results from 200 billion iris pair comparisons. Proceedings of the IEEE, 94(11)
  16. L. Ma, T. Tan (2003) Y. Wang, and D. Zhang "Personal identification based on iris texture analysis," IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(12), 1519–1533
  17. J. E. Gentile, N. Ratha, and J. Connell. (2009) SLIC : Short-length iris codes. IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems (BTAS),
  18. H. Sung, J. Lim, Y. Lee (2004) "Iris recognition using collarette boundary localization," Proceeding of the 17th International conference on pattern recognition
  19. LiYu,,D. Zhang, K. Wang,W. Yang (2005) " Coarse iris classification using box-counting to estimate fractal dimensions" Elsevier Journal of Pattern Recognition, 38 1791 – 1798
  20. LiYu,, K. Wang, D. Zhang (2005) " Coarse iris classification using box-counting method" IEEE Conference on Image Processing(ICIP), . 3 301-304
  21. "CASIA Iris Image Database," http://www. sinobiometrics. com
  22. R. Kohavi,F. Provost (1998) "On applied research on Machine Learning" Kluwer academic Publishers. Boston 30,127-132
Index Terms

Computer Science
Information Sciences

Keywords

Iris Classification Fractal Dimensions Double Threshold Algorithm

Powered by PhDFocusTM