CFP last date
20 December 2024
Reseach Article

Personal Authentication through Retinal Blood Vessels Intersection Points Matching

by Md. Amran Siddiqui, S. M. Hasan Sazzad Iqbal, Md. Rounok Salehin
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 33 - Number 9
Year of Publication: 2011
Authors: Md. Amran Siddiqui, S. M. Hasan Sazzad Iqbal, Md. Rounok Salehin
10.5120/4052-5816

Md. Amran Siddiqui, S. M. Hasan Sazzad Iqbal, Md. Rounok Salehin . Personal Authentication through Retinal Blood Vessels Intersection Points Matching. International Journal of Computer Applications. 33, 9 ( November 2011), 34-39. DOI=10.5120/4052-5816

@article{ 10.5120/4052-5816,
author = { Md. Amran Siddiqui, S. M. Hasan Sazzad Iqbal, Md. Rounok Salehin },
title = { Personal Authentication through Retinal Blood Vessels Intersection Points Matching },
journal = { International Journal of Computer Applications },
issue_date = { November 2011 },
volume = { 33 },
number = { 9 },
month = { November },
year = { 2011 },
issn = { 0975-8887 },
pages = { 34-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume33/number9/4052-5816/ },
doi = { 10.5120/4052-5816 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:19:47.358861+05:30
%A Md. Amran Siddiqui
%A S. M. Hasan Sazzad Iqbal
%A Md. Rounok Salehin
%T Personal Authentication through Retinal Blood Vessels Intersection Points Matching
%J International Journal of Computer Applications
%@ 0975-8887
%V 33
%N 9
%P 34-39
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents a method of personal authentication process using digital retinal image matching. The process composed of four modules: reference point’s detection, blood vessel segmentation and derivation of corresponding binary image skeleton of one pixel width, feature points extraction and finally matching similarities among these feature points of different images. The Fovea center and the Optic disc are used as reference points for compensating the unwanted rotational and translational effects. The maximum principal curvature of the Hessian matrix of the intensity image is used along with some image filtering to segment the blood vessel structure. Then the skeleton of the binary image and corresponding blood vessel intersection points are extracted using two proposed algorithms. Finally the matching process is done by proximity analysis of the intersection points of different retinal images. The whole process is then tested on several retinal images of different persons and the tested images were classified correctly.

References
  1. K. Jain, L. Hong and S. Pankanti, “Biometrics: Promising Frontiers for Emerging Identification Market,” Communication of the ACM, pp. 91-98, February 2000.
  2. A. K. Jain, L. Hong, S. Pankanti, and R. Bolle, “An identityauthentication system using fingerprints,” Proceedings of the IEEE, vol. 85, no. 9, pp. 1365–1388, 1997.
  3. Anil Jain, Arun Ross, Salil Prabhakar, “Fingerprint Matching Using Minutiae and Texture Features”, Proc. of ICIP, pp. 282-285, 2001M.
  4. 4 J. G. Daugman, “Biometric personal identification system based on iris analysis,” US patent no. 5291560, 1994.
  5. H. Farzin, H. Abrishami-Moghaddam, and M.-S. Moin, “A novel retinal identification system,” EURASIP Journal on Advances in Signal Processing, vol. 2008, Article ID 280635, 10 pages, 2008.
  6. M. Ortega, MG Penedo, J. Rouco, N. Barreira, and MJ Carreira, “Retinal verification using a feature points-based biometric pattern,” EURASIP Journal on Advances in Signal Processing, vol. 2009, p. 13 pages, 2009.
  7. S M Raiyan Kabir, Rezwanur Rahman, Mursalin Habib and M Rezwan Khan, Person Identification by Retina Pattern Matching, ICECE, pages 522-525, December 2004.
  8. C. Mari˜no, M. G. Penedo, M. Penas, M. J. Carreira, and F. Gonz´alez, “Personal authentication using digital retinal images,” Pattern Analysis and Applications, vol. 9, no. 1, pp. 21–33, 2006.
  9. C. Mari˜no, M. G. Penedo, M. J. Carreira, and F. Gonz´alez, “Retinal angiography based authentication,” in Proceedings of the 8th Iberoamerican Congress on Pattern Recognition (CIARP’03), vol. 2905 of Lecture Notes in Computer Science, pp. 306–313, Havana, Cuba, November 2003.
  10. S. Nanavati, M. Thieme and R. Nanavati, Biometrics Identity Verification in a Networked World, John Wiley & Sons, Inc., 2002.
  11. R. C. Gonzalez and R. E. Woods, Digital Image Processing., Pearsons Education Inc., 2005 Second Edition.
  12. M. E. Martinez-Perez, A. D. Hughes, A. V. Stanton, S. A. Thom, A. A. Bharath and K. H. Parker. Retinal blood vessel segmentation by means of scale-space analysis and region growing. Lecture Notes in Computer Science. Medical Image Computing and Computer-Assisted Intervention (MICCAI'99). Vol. 1679. 19-22th September, 1999. Cambridge, England, pp. 90-97.
  13. Sameh A. Salem, Nancy M. Salem, and Asoke K. Nandi, Segmentation of retinal blood vessels using a novel clustering algorithm, European Signal Proccesing Conference EUSIPCO 2006.
Index Terms

Computer Science
Information Sciences

Keywords

Biometric personal authentication Fovea center detection Optic disc detection Retina blood vessel skeleton generation Blood vessel intersection point detection Blood vessel segmentation