CFP last date
22 April 2024
Reseach Article

Improved Iris Recognition in 2D Eigen Space

by Abhijit Das, Ranjan Parekh
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 52 - Number 19
Year of Publication: 2012
Authors: Abhijit Das, Ranjan Parekh
10.5120/8314-1247

Abhijit Das, Ranjan Parekh . Improved Iris Recognition in 2D Eigen Space. International Journal of Computer Applications. 52, 19 ( August 2012), 1-6. DOI=10.5120/8314-1247

@article{ 10.5120/8314-1247,
author = { Abhijit Das, Ranjan Parekh },
title = { Improved Iris Recognition in 2D Eigen Space },
journal = { International Journal of Computer Applications },
issue_date = { August 2012 },
volume = { 52 },
number = { 19 },
month = { August },
year = { 2012 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume52/number19/8314-1247/ },
doi = { 10.5120/8314-1247 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:52:43.542367+05:30
%A Abhijit Das
%A Ranjan Parekh
%T Improved Iris Recognition in 2D Eigen Space
%J International Journal of Computer Applications
%@ 0975-8887
%V 52
%N 19
%P 1-6
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper a new biometric method for personal identification is been presented by iris identification of a person in lower dimensionality and reduced template size than the other previous approaches in 2D Eigen space, so that it can be use for verification in application areas . Here the iris images are expressed in lower dimension, re-tending its features by using covariance matrix and Eigen matrix to a covariant-Eigen space vector. The proposed approach is also suitable to work on half iris image. The proposed approach shows high accurate result.

References
  1. Bertillon, A, 1885. La couleur de Piris. Revue scientifique. Vol. 36, No. 3, 65-73.
  2. Daugman, J. 1992. High confidence personal identification by rapid video analysis of iris Texture. Proc. IEEE International Carnaha conf. on security technology, 50-60.
  3. Daugman, J. 1993. High confidence visual recognition of persons by a test of statistical independence. IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 15, No. 11, 1148-1161.
  4. Daugman, J. 2004. How iris recognition works. Circuits and Systems for Video Technology. IEEE Trans. , Vol. 14, No. 1, 21-30.
  5. Daugman, J. 2007. New Methods in Iris Recognition. Proc. IEEE Trans. on system, man and cybernetics-part B, Vol. 37, No 5, 1167-1175.
  6. Savithiri, G. , and Murugan, A. 2011. Performance Analysis on Half Iris Feature Extraction using GW, LBP and HOG. International Journal of Computer Applications, Vol. 22, No. 2 (May 2011), 27-32.
  7. Hussain, Md. A. 2010. Eigenspace Based Accurate Iris Recognition System. Proc. Annual IEEE India Conference (INDICON), 763-767.
  8. Monro, D. M. , Rakshit, S. , and Zhang, D. 2007. DCT-Based Iris Recognition. IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 29, No. 3 (April 2007), 586-595.
  9. Das, A. , and Parekh, R. 2012. Iris Recognition using a Scalar base Template in Eigen-space. IJCST, Vol. 3, No. 5, 74-79.
  10. Wang, Q, Zhang, X. , Li, M. , Dong, X. , Zhou, Q. , and Yin, Y. 2012. Adaboost and multi-orientation 2D Gabor-based noisy iris recognition. Pattern Recognition Letters, Vol. 33, 978–983.
  11. Roy, K. , and Bhattacharya, P. 2007. Iris Recognition Based on Zigzag Collarette Region and Asymmetrical Support Vector Machines. International Conference on Image Analysis and Recognition, 854–865.
  12. Wang, L. , Yang, G. , and Yin, Y. 2010. Fast Iris Localization Based on Improved Hough Transform. Rough Set and Knowledge Technology, 439–446.
  13. Nabti, M. and Bouridane, A. 2007. An Improved Iris Recognition System Using Feature Extraction Based on Wavelet Maxima Moment Invariants. International Conference on Biometrics, 988 – 996.
  14. Roy, K. , Bhattacharya, P. , and Ching, Y. S. 2011. Iris recognition using shape-guided approach and game theory. Pattern Anal Application, Vol. 14, 329–348.
  15. Radman, A. , Jumari, K. , and Zainal, N. 2011. Iris Segmentation: A Review and Research Issues. International Conference on Software Engineering and Computer Systems, 698–708.
  16. Woodard, D. L. , Pundlik, S. J. , Miller,P. E. , and Lyle, J. R. 2011. Appearance-based periocular features in the context of face and non-ideal iris recognition. Signal, Image and Video Processing, Vol. 5, 443–455.
  17. Luis Miguel Zamudio-Fuentes1, Mireya S. García-Vázquez, and Alejandro Alvaro Ramírez-Acosta 2011. Local Quality Method for the Iris Image Pattern. Computer Analysis of Images and Patterns, 79–88.
  18. Martinez, F. , Carbone, A. , and Pissaloux, E. 2011. Radial Symmetry Guided Particle Filter for Robust Iris Tracking. Computer Analysis of Images and Patterns, 531–539.
  19. Erdogmus, N. , and Dugelay, J. 2010. An Efficient Iris and Eye Corners Extraction Method. Structural, Syntactic, and Statistical Pattern Recognition, 549–558.
  20. Abidin, Z. Z. , Manaf, M. , and Shibghatullah, A. S. 2011. A New Model of Securing Iris Authentication Using Steganography. International Conference on Software Engineering and Computer Systems, 547–554.
  21. CASIA Iris Image Database Version 3. 0 (CASIA-IrisV3), Available: www. biometrics. idealtest. org
Index Terms

Computer Science
Information Sciences

Keywords

Covariance matrix Eigen matrix Covariant-Eigen space