Experimental Study on the Effect of Pattern Variation and Feature Points on Fingerprint Matching
DOI:
https://doi.org/10.24203/ijcit.v12i2.325Keywords:
fingerprint, pattern variation, singular point, features, matching.Abstract
Fingerprint has been adjudged as the most reliable means of identification and authentication of an individual because of its uniqueness, high immutability and unchanging patterns. Typically, the ridges of fingers consist of different pattern types whose attributes are often extracted for matching during fingerprint classification. The occurrence of these patterns vary among fingerprint, which has significantly affected the accuracy of fingerprint recognition and classification processes. This paper therefore focuses on the investigation of the impact of pattern variation, singular points and feature points on fingerprint matching. The investigation was based on benchmarked FVC2000, FVC2002, FVC2004 and FVC2006 fingerprint databases which comprise four datasets each from different sources and of varied types. The obtained false non match rate (FNMR), false match rate (FMR), total matching time (TMT) and average matching time (AMT) values revealed that use of multiple matching criteria will lead to extension in the fingerprint matching time.
References
S.O.Ogunlana, G.B Iwasokun, and O. Olatubosun, Fingerprint Individuality Model Based on Pattern Type and Singular Point Attributes, International Journal of Information Security Science, Vol. 10, No.3, pp.75-85, 2021. [2] G.B. Iwasokun and O.C. Akinyokun, Fingerprint Singular Point Detection Based on Modified Poincare Index Method, International Journal of Signal Processing, Image Processing and Pattern Processing, Vol.7, No.5, pp259-272, 2014.[3] A.K. Jain, J. Feng, and K. Nandakumar, Fingerprint Matching. IEEE Computer Society. pp. 36-44. 2010[4] O. C. Akinyokun, B.K. Alese, and G.B. Iwasokun, Fingerprint Matching using Spatial Characteristics. Proceedings of the World Congress on Engineering. Vol 1, July 2-4. 2014[5] S.O. Ogunlana, Pattern Analysis Model for the Investigation of Fingerprint Individuality. Ph.D Thesis, Department of Computer Science, Federal University of Technology, Akure, Nigeria. 2021. [6] G.B. Iwasokun, Fingerprint Matching Using Minutiae-Singular Points Network. International Journal of Signal Processing, Image Processing and Pattern Recognition. Vol. 8, No. 2, pp. 375-388. 2015.[7] V. Awasthi,, A. Vanchha and K. Tiwari, Fingerprint Analysis using Termination and Bifurcation minutiae, International journal of Emerging Technology and Advanced Engineering. ISSN 2250-2459. Vol.2, Issue 2, pp.124-130. 2012.[8] Y. He, J. Tian, L. Li, H. Chen, and X. Yang, Fingerprint Matching based on Global Comprehensive Similarity. IEEE Transaction on Pattern Analysis and Machine Intelligence, 28(6). 2006.[9] M.U. Munir, and M.Y. Javed, Fingerprint Matching using Ridge Patterns. IEEE, pp. 116-120. 2005.[10] J. Wang, Finger image Quality Based on Singular Point Localization. M Sc thesis submitted at the department of Information and Mathematical Modelling, Technical University, Denmark, 2013.[11] M. Shahram and F. Ali, A Matching Algorithm of Minutiae for Real Time Fingerprint Identification System, World Academy of Science, Engineering and Technology. Vol, 60, pp. 595-599, 2009. [12] S. Yadav, and M. Mathuria, Fingerprint Recognition Based on Minutiae Information, International Journal of Computer Applications. Vol. 120, No. 10, pp. 39-42. 2015.[13] G.B. Iwasokun, Development of a Hybrid Platform for Pattern Recognition and Matching of Thumbprints, PhD Thesis, Department of Computer Science, Federal University of Technology, Akure, 2012.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Oluwatayo Samuel Ogunlana, Gabriel Babatunde Iwasokun
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
The articles published in International Journal of Computer and Information Technology (IJCIT) is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
