Fingerprint Verification System Using Combined Minutiae and Cross Correlation Based Matching
American Journal of Electrical and Computer Engineering
Volume 2, Issue 2, December 2018, Pages: 16-26
Received: May 22, 2018;
Accepted: Jun. 20, 2018;
Published: Nov. 27, 2018
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Akinleye Okedola Akinyele, Department of Computer Engineering, Lagos State Polytechnic, Lagos, Nigeria
Adegbola Jamiu Sarumi, Department of Computer Engineering, Lagos State Polytechnic, Lagos, Nigeria
Badmus Abdulsamad, Department of Electrical/Electronics, University of Lagos, Lagos, Nigeria
Olawole Olakunle Green, Department of Computer Engineering, Lagos State Polytechnic, Lagos, Nigeria
An effective system to verify human identity is a major challenge in most traditional access control systems in developing countries, as it can easily be compromised. From the vulnerability of banking transactions to the multiple registration in most civic identification projects like voters’ registration, Payroll System and Pension Scheme underscores the urgent need for an effective system that provide immediate technological solution. This research work presents an Automated Fingerprint Verification System simulating both Minutiae Based Matching and Cross Correlation Coefficient Matching that provides an effective and efficient means of verifying human identity which significantly decreases the possibility of fraud in access control. The method used MATLAB simulation to align the minutiae of the two-fingerprint image (query template) and stored templates (reference template) inputted to find the total number of minutiae matched. After alignment, two minutiae are considered for matching when spatial distance and direction difference between them are not up to a given tolerance. Finally, the templates were further verified with cross correlation algorithm to improve the result accuracy. This approach has better performance as compared to individual matching technique. The result obtained after testing several fingerprints for identification proved to be efficient by verifying correctly the identities of the persons enrolled and achieving a matching score above 80% threshold for Matching Pair and below 80% threshold for Non-Matching Pair.
Akinleye Okedola Akinyele,
Adegbola Jamiu Sarumi,
Olawole Olakunle Green,
Fingerprint Verification System Using Combined Minutiae and Cross Correlation Based Matching, American Journal of Electrical and Computer Engineering.
Vol. 2, No. 2,
2018, pp. 16-26.
Copyright © 2018 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/
) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Langenburg Gkenn, “Are one’s fingerprints similar to those of his or her parents in any discernable way?” Scientist American, Springer Nature, January 24, 2005. Available: “http://www.scientificamerican.com/article.cfm?id=are-ones-fingerprints-sim”. [Retrieved: 30 November 2016].
Lawrence O’ Gorman, “Fingerprint Verification”, Veridicom Incorporation, Springer International Publishing, October 2006 Available:“https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=2&cad=rja&uact=8&ved=0ahUKEwiene7fr9DQAhVkL8AKHfmQDVcQFggiMAE&url=http%3A%2F%2Flink.springer.com%2Fchapter%2F10.1007%252F0-306-47044-6_2&usg=AFQjCNFKayQNVhAilWHio4OBW_O_fgthng&sig2=gaKqdd-BLPhdjjGv7-Vqng”. [Accessed: 29th November 2016].
Sangram Bana, et al, “Fingerprint Recognition using Image Segmentation”, Research Gate, (IJAEST) International Journal of Advanced Engineering Sciences and Technologies, Volume No 5, Issue No 1, 012-023. [October 13 2016]. Available:https://www.researchgate.net/publication/228422763_Fingerprint_Recognition_using_Image_Segmentation. [Accessed: November 30, 2016].
Justice MuhammedLawalGarba, et al, ”Full Text of the Judgment of Aregbeshola versus oyinlola”, Nigerian muse, Court of Appeal, Ibadan Judiciary Division, [26th November 2010],Avaliable:”www.nigerianmuse.com/20101201041725zg/sections/general-articles/full-text-of-the-judgment-of-appeal-of-aregbesola-vs-oyinlola-delivered-nov-26-2010-by-justice-ogunbiyi-et-al/”. [Accessed: 28th November, 2016].
Kenneth R. Moses, et al, “Automated Fingerprint Identification System”, United States office of the Justice Programs, National Criminal Justice Reference Service, [October 2014]. Available: “https://www.ncjrs.gov/pdffiles1/nij/225326.pdf”. [Accessed: 30th November 2016]
Setlak, Dale, “Advances in Biometric Fingerprint Technology and Driving Rapid Adoption in consumer marketplace”, Wikipedia, AuthenTec, [Retrieved: 4 November, 2010]. Available:”https://docs.google.com/viewer?url=www.authentec.com%2Fdocs%2Fwhite%2520paper%2520for%2520ziffdavis.doc”.[Accessed: 28th November, 2016]
J. L Wayman et al, “Technical Testing and Evaluation of Biometric Devices”, 360 biometrics, [September 2011], Available:” http://www.360biometrics.com/fingerprint-scanners/hamsterplus.php”.[Accessed: 30th October, 2016]
M. J Stephen, “Removal of false minutia with modified fuzzy rules”, Research Gate, Welfare Institute of Science Technology and Management, [July 2013], Available: “https://www.researchgate.net/publication/256470785_Removal_of_False_Minutiae_with_Modified_Fuzzy_Rules”. [Accessed: 30th November, 2016]
Dario Maio et al, ” Performance Evaluation of Fingerprint Verification System”, Research Gate, Department of Computer Science and Engineering, University of Bologna, [February, 2006], Available: https://www.researchgate.net/publication/7368583_Performance_evaluation_of_fingerprint_verification_systems. [Accessed: 29th November, 2016]
Gabriel Iwasokun et al, “An Investigation into Impact of False Minutia Points on Fingerprint Matching”, Research Gate, Federal University of Akure, Department of Computer Science, [June 2014], Available: https://www.researchgate.net/publication/284631114_An_Investigation_into_the_Impact_of_False_Minutiae_Points_on_Fingerprint_Matching. [Accessed: 30th November, 2016]
A. M. Baze, G. T. B Verwaaijen, S. H. Garez, L. P. J. Veelunturf, and B. J. van der Zwaag.A correlation-based fingerprint verification system. In ProRISC2000 Workshops on Circuits,Systems and Signal Processing, Nov 2000.