A Review: Person Identification using Retinal Fundus Images
Abstract
In this paper a review on biometric person identification has been discussed using features from retinal fundus image. Retina recognition is claimed to be the best person identification method among the biometric recognition systems as the retina is practically impossible to forge. It is found to be most stable, reliable and most secure among all other biometric systems. Retina inherits the property of uniqueness and stability. The features used in the recognition process are either blood vessel features or non-blood vessel features. But the vascular pattern is the most prominent feature utilized by most of the researchers for retina based person identification. Processes involved in this authentication system include pre-processing, feature extraction and feature matching. Bifurcation and crossover points are widely used features among the blood vessel features. Non-blood vessel features include luminance, contrast, and corner points etc. This paper summarizes and compares the different retina based authentication system. Researchers have used publicly available databases such as DRIVE, STARE, VARIA, RIDB, ARIA, AFIO, DRIDB, and SiMES for testing their methods. Various quantitative measures such as accuracy, recognition rate, false rejection rate, false acceptance rate, and equal error rate are used to evaluate the performance of different algorithms. DRIVE database provides 100\% recognition for most of the methods. Rest of the database the accuracy of recognition is more than 90\%.References
S. Pal, U. Pal, and M. Blumenstein, “Signature-based biometric authentication,” Studies in Computational Intelligence, vol. 555, pp. 285–314, Jan. 2014.
M. M. H. Ali, V. H. Mahale, P. Yannawar, and A. T. Gaikwad, “Overview of fingerprint recognition system,” in 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT), Mar. 2016, pp. 1334–1338.
H. Shah, M. Ab Rashid, M. F. Abdollah, M. N. Kamarudin, C. Lin, and Z. Kamis, “Biometric voice recognition in security system,” Indian
Journal of Science and Technology.
J. Soldera, G. Schu, L. R. Schardosim, and E. T. Beltrao, “Facial biometrics and applications,” IEEE Instrumentation Measurement Magazine, vol. 20, no. 2, pp. 4–30, April 2017.
J. Liu-Jimenez, R. Sanchez-Reillo, and B. Fernandez-Saavedra, “Iris biometrics for embedded systems,” IEEE Transactions on Very Large
Scale Integration (VLSI) Systems, vol. 19, no. 2, pp. 274–282, Feb 2011.
Z. Zhou, E. Y. Du, N. L. Thomas, and E. J. Delp, “A new human identification method: Sclera recognition,” IEEE Transactions on Systems,
Man, and Cybernetics - Part A: Systems and Humans, vol. 42, no. 3, pp. 571–583, May 2012.
C. Simon and I. Goldstein, “A new scientific method of identification,” New York State Journal of Medicine, vol. 35, no. 18, pp. 901–906, 1935.
P. Tower, “The fundus oculi in monozygotic twins: report of six pairs of identical twins,” Archives of Ophthalmology, vol. 54, pp. 225–239, 1955.
A. K. Jain, A. Ross, and S. Prabhakar, “An introduction to biometric recognition,” IEEE Transactions on circuits and systems for video
technology, vol. 14, no. 1, pp. 4–20, 2004.
E. Poonguzhali, R. Giritharan, M. K. Nath, and O. P. Acharya, “Review on localization of optic disc in retinal fundus images,” in International Conference on Applied Electromagnetics, Signal Processing and Communication (AESPC), Oct. 2018.
Z. Waheed, M. U. Akram, A. Waheed, M. A. Khan, A. Shaukat, and M. Ishaq, “Person identification using vascular and non-vascular retinal features,” Computers and Electrical Engineering, vol. 53, pp. 359 – 371, 2016.
S. Moccia, E. D. Momi, S. E. Hadji, and L. S. Mattos, “Blood vessel segmentation algorithms — review of methods, datasets and evaluation metrics,” Computer Methods and Programs in Biomedicine, vol. 158, pp. 71 – 91, 2018.
H. Farzin, H. Abrishami-Moghaddam, and M.-S. Moin, “A novel retinal identification system,” EURASIP Journal on Advances in Signal Processing, vol. 2008, no. 1, Apr. 2008.
M. Akram, A. Tariq, and S. Khan, “Retinal recognition: Personal identification using blood vessels,” 2011 International Conference for
Internet Technology and Secured Transactions, ICITST 2011.
J. Fatima, A. M. Syed, and M. Akram, “A secure personal identification system based on human retina,” in ISIEA 2013 - 2013 IEEE Symposium on Industrial Electronics and Applications, Sep. 2013, pp. 90–95.
R. K. Gharami and M. K. Nath, “A new approach to biometric person identification from retinal vascular patterns,” Emerging Trends and Technology in Computer Science (IJETTCS), vol. 3, no. 5, pp. 191–195, Sep. 2014.
Z. Waheed, M. U. Akram, A. Waheed, M. A. Khan, A. Shaukat, and M. Ishaq, “Person identification using vascular and non-vascular retinal features,” Computers and Electrical Engineering, vol. 53, 2016.
F. Jiu, K. Noronha, and D. Jayaswal, “Biometric identification through detection of retinal vasculature,” 2016 IEEE 1st International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES), pp. 1–5, 2016.
A. Bhuiyan, A. Hussain, A. Mian, T. Y. Wong, K. Ramamohanarao, and Y. Kanagasingam, “Biometric authentication system using retinal vessel pattern and geometric hashing,” IET Biometrics, vol. 6, no. 2, pp. 79–88, 2017.
U. T. V. Nguyen, A. Bhuiyan, L. A. F. Park, and K. Ramamohanarao, “An effective retinal blood vessel segmentation method using multi-scale line detection,” Pattern Recognition, vol. 46, no. 3, pp. 703 – 715, 2013.
N. A. Rahman, A. S. Mohamed, and M. E. Rasmy, “Retinal identification,” in 2008 Cairo International Biomedical Engineering Conference, Dec. 2008, pp. 1–4.
M. Sabaghi, S. R. Hadianamrei, M. Fattahi, M. R. Kouchaki, and A. Zahedi, “Retinal identification system based on the combination
of fourier and wavelet transform,” Journal of Signal and Information Processing, vol. 03, no. 01, 2012.
A. Dehghani, Z. Ghassabi, H. A. Moghddam, and M. S. Moin, “Human recognition based on retinal images and using new similarity function,” EURASIP Journal on Image and Video Processing, vol. 2013, no. 01, Oct. 2013.
H. Tabatabaee and H. Jafariani, “Retinal identification system using fourier-mellin transform and fuzzy clustering,” Indian Journal of Science and Technology.
Z. Waheed, A. Waheed, and M. U. Akram, “A robust non-vascular retina recognition system using structural features of retinal image,” in 2016 13th International Bhurban Conference on Applied Sciences and Technology (IBCAST, Jan. 2016, pp. 101–105.
M. Modarresi, I. S. Oveisi, and M. Janbozorgi, “Retinal identification using shearlets feature extraction,” Austin Biometrics and Biostatistics, vol. 4, 2017.
M. M. Asem and I. S. Oveisi, “Biometric retinal authentication based on multi-resolution feature extraction using mahalanobis distance,” Biometrics and Biostatistics International Journal.
R. Mukundan, S. H. Ong, and P. A. Lee, “Image analysis by tchebichef moments,” IEEE Transactions on Image Processing, vol. 10, no. 9, pp.1357–1364, Sep. 2001.
W.-Q. Lim, “The discrete shearlet transform: A new directional transform and compactly supported shearlet frames,” IEEE Transactions on Image Processing, vol. 19, no. 5, pp. 1166–1180, May. 2010.
M. N. Do and M. Vetterli, “The contourlet transform: an efficient directional multiresolution image representation,” IEEE Transactions on Image Processing, vol. 14, no. 12, pp. 2091–2106, Dec 2005.
J. Staal, M. D. Abramoff, M. Niemeijer, M. A. Viergever, and B. van Ginneken, “Ridge-based vessel segmentation in color images of the
retina,” IEEE Transactions on Medical Imaging, vol. 23, no. 4, pp. 501– 509, April 2004.
A. Hoover and M. Goldbaum, “Locating the optic nerve in a retinal image using the fuzzy convergence of the blood vessels,” IEEE Transactions on Medical Imaging, vol. 22, no. 8, pp. 951–958, Aug 2003.
D. J. J. Farnell, F. N. Hatfield, P. Knox, M. Reakes, D. Parry, and S. P. Harding, “Enhancement of blood vessels in digital fundus photographs via the application of multiscale line operators,” Journal of the Franklin Institute, vol. 345, no. 7, pp. 748 – 765, 2008.
RIDB, “Retinal identification databases,” www.biomisa.org/RIDB.
P. Prentasic, S. Loncaric, Z. Vatavuk, G. Bencic, M. Subasic, T. Petkovic, L. Dujmovic, M. M.-R. N. Budimlija, and R. Tadic, “Diabetic retinopathy image database(dridb): A new database for diabetic retinopathy screening programs research,” in 2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA), Sep. 2013, pp. 711–716.
M. Ortega, M. Penedo, J. Rouco, N. Barreira, and M. Carreira, “Personal verification based on extraction and characterisation of retinal feature points,” Journal of Visual Languages and Computing, vol. 20, no. 2, pp. 80 – 90, 2009.
VARIA, “Varpa retinal images for authentication,” http://www.varpa.es/varia.html.
Downloads
Published
Issue
Section
License
Copyright (c) 2019 International Journal of Electronics and Telecommunications

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
1. License
The non-commercial use of the article will be governed by the Creative Commons Attribution license as currently displayed on https://creativecommons.org/licenses/by/4.0/.
2. Author’s Warranties
The author warrants that the article is original, written by stated author/s, has not been published before, contains no unlawful statements, does not infringe the rights of others, is subject to copyright that is vested exclusively in the author and free of any third party rights, and that any necessary written permissions to quote from other sources have been obtained by the author/s. The undersigned also warrants that the manuscript (or its essential substance) has not been published other than as an abstract or doctorate thesis and has not been submitted for consideration elsewhere, for print, electronic or digital publication.
3. User Rights
Under the Creative Commons Attribution license, the author(s) and users are free to share (copy, distribute and transmit the contribution) under the following conditions: 1. they must attribute the contribution in the manner specified by the author or licensor, 2. they may alter, transform, or build upon this work, 3. they may use this contribution for commercial purposes.
4. Rights of Authors
Authors retain the following rights:
- copyright, and other proprietary rights relating to the article, such as patent rights,
- the right to use the substance of the article in own future works, including lectures and books,
- the right to reproduce the article for own purposes, provided the copies are not offered for sale,
- the right to self-archive the article
- the right to supervision over the integrity of the content of the work and its fair use.
5. Co-Authorship
If the article was prepared jointly with other authors, the signatory of this form warrants that he/she has been authorized by all co-authors to sign this agreement on their behalf, and agrees to inform his/her co-authors of the terms of this agreement.
6. Termination
This agreement can be terminated by the author or the Journal Owner upon two months’ notice where the other party has materially breached this agreement and failed to remedy such breach within a month of being given the terminating party’s notice requesting such breach to be remedied. No breach or violation of this agreement will cause this agreement or any license granted in it to terminate automatically or affect the definition of the Journal Owner. The author and the Journal Owner may agree to terminate this agreement at any time. This agreement or any license granted in it cannot be terminated otherwise than in accordance with this section 6. This License shall remain in effect throughout the term of copyright in the Work and may not be revoked without the express written consent of both parties.
7. Royalties
This agreement entitles the author to no royalties or other fees. To such extent as legally permissible, the author waives his or her right to collect royalties relative to the article in respect of any use of the article by the Journal Owner or its sublicensee.
8. Miscellaneous
The Journal Owner will publish the article (or have it published) in the Journal if the article’s editorial process is successfully completed and the Journal Owner or its sublicensee has become obligated to have the article published. Where such obligation depends on the payment of a fee, it shall not be deemed to exist until such time as that fee is paid. The Journal Owner may conform the article to a style of punctuation, spelling, capitalization and usage that it deems appropriate. The Journal Owner will be allowed to sublicense the rights that are licensed to it under this agreement. This agreement will be governed by the laws of Poland.
By signing this License, Author(s) warrant(s) that they have the full power to enter into this agreement. This License shall remain in effect throughout the term of copyright in the Work and may not be revoked without the express written consent of both parties.