International Journal of Computer
Trends and Technology

Research Article | Open Access | Download PDF

Volume 17 | Number 1 | Year 2014 | Article Id. IJCTT-V17P127 | DOI : https://doi.org/10.14445/22312803/IJCTT-V17P127

Retina based Personal Identification System using Skeletonization and Similarity Transformation

Geethu Sasidharan

Citation :

Geethu Sasidharan, "Retina based Personal Identification System using Skeletonization and Similarity Transformation," International Journal of Computer Trends and Technology (IJCTT), vol. 17, no. 1, pp. 144-147, 2014. Crossref, https://doi.org/10.14445/22312803/IJCTT-V17P127

Abstract

Biometric security has become more important because of the increasing activities of terrorists and hackers. One of the most reliable biometric security systems is retina biometric security system, because no two people have the same retinal pattern. The proposed system consist of four modules viz, retina fundus acquisition, Pre-processing, Detection of bifurcation points and Feature matching. In the pre-processing step retinal blood vessels are enhanced and segmented. From the segmented image bifurcation points are detected, with the help of skeleton process. Using this bifurcation points, it check similarity with bifurcation points of reference images in database using similarity transformation. The proposed system has extremely lower error rate and quick response.

Keywords

Retina biometric, Frangi’s vessel detection, Skeletonization, Similarity transformation.

References

[1] Robust Vessel Segmentation in Fundus Images, A. Budai, R. Bock, A. Maier, J. Hornegger, and G.Michelson. Hindawi Publishing Corporation International Journal of Biomedical Imaging Volume 2013, Article ID 154860, 11 pages http://dx.doi.org/10.1155/2013/154860
[2] A Combined Method to Detect Retinal Fundus Features V. Bevilacqua S. Cambo L. Cariello G. Mastronardi, Politecnico Di Bari (Italy)
[3] Retinal Verification Using a Feature Points-Based Biometric Pattern, M. Ortega, M. G. Penedo, J. Rouco, N. Barreira, and M. J. Carreira, Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2009, Article ID 235746, 13 pages doi:10.1155/2009/235746.
[4] Alejandro F. Frangi,Wiro J.Niessen, et al. “Multiscale vessel enhancement filtering,” Medical Image Computing and computer-Assisted Intervation-MICCAI’98. 1998,1496:130:137.
[5] Digital image processing, third edition, Rafael C Gonzales and Richard E Woods.
[6] Retinal Fundus Biometric Analysis for Personal Identifications, Vitoantonio Bevilacqua, Lucia Cariello, Donatello Columbo, Domenico Daleno, Massimiliano Dellisanti Fabiano, Marco Giannini, Giuseppe Mastronardi, and Marcello Castellano, D.-S. Huang et al. (Eds.): ICIC 2008, LNAI 5227, pp. 1229–1237, 2008.
[7] Retinal Fundus Features Hybrid Detection based on a Genetic Algorithm, Vitoantonio Bevilacqua, Lucia Cariello, Simona Cambo, Domenico Daleno, Giuseppe Mastronardi, DEE Polytechnic of Bari, Via Orabona 4, 70125 Bari, Italy
[8] Bevilacqua ,V., Cariello, L., Introna, F., Mastronardi, G., 2005, A Genetic Algorithm Approach to Detect Eye Fundus Vessel Bifurcation Points, Proceedings of Int. Conference, CIMED’2005, Lisbon ISBN 0-86341-520-2, pp.355-360.
[9] A Survey on Biometric Recognition Techniques, ARULALAN.V, BALAMURUGAN.G, PREMANAND. V, International Journal of Advanced Research in Computer and Communication Engineering Vol. 3, Issue 2, February 2014.
[10] Extraction of the Retinal Blood Vessels and Detection of the Bifurcation Points, Manjiri B. Patwa, Dr. Remesh R. Manza, Yogesh M. Rajput, Dr. Neha K. Despande and Dr. Manoj Saswade. International Journal of Computer Applications (0975 – 8887) Volume 77– No.2, September 2013.