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Annals of Computer Science and Information Systems, Volume 13

Communication Papers of the 2017 Federated Conference on Computer Science and Information Systems

Identification of Fingerprints using Circular String Approximation for Mobile Devices

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DOI: http://dx.doi.org/10.15439/2017F3

Citation: Communication Papers of the 2017 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 13, pages 193197 ()

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Abstract. Lately, Biometrics has employed the use of fingerprints to identify individuals. Out of the commonly used techniques, fingerprint authentication till date, remains the most reliable. The bulk of research that has focused on fingerprint authentication, has however, neglected the issues that arise with fingerprints resulting to incorrect orientation identification. This is because it is assumed and often times wrongly, that the direction of the fingerprint will align with the stored fingerprint image. This singular issue poses tension in fingerprint matching, which only a negligible number of techniques have considered. As computers and mobile devices adopt fingerprint recognition as a way to authenticate user, this apparent tension gains more popularity, becoming an integral research area which must be addressed.


  1. Ajala, O., Aljamea, M., Alzamel, M., Iliopoulos, C. S., Fast Fingerprint Rotation Recognition Technique Using Circular Strings in Lexicographical Order. SAI Intelligent Systems Conference 2016, September 21-22, 2016, London, UK
  2. Ajala, O., Aljamea, M., Alzamel, M., Iliopoulos, C. S., Strigini, Y., Fast Fingerprint Recognition Using Circular String Pattern Matching Techniques. PATTERNS 2016 : The Eighth International Conferences on Pervasive Patterns and Applications
  3. Al-Jamea, M et al, 2015. A Novel Pattern Matching Approach for Fingerprint-based Authentication. PATTERNS 2015: The Seventh International Conferences on Pervasive Patterns and Applications, [Online]. 978-1-61208-393-3, 45-49. Available at: https://www.thinkmind.org/download.php?articleid=patterns_2015_2_40 70032 [Accessed 12 March 2016].
  4. Angle, S et al, 2005. Biometrics: A Further Echelon of Security. The Im­pact of Technology on Plagiarism Prevention and Detection: Re­search Process Automation, a New Approach for Preven tion, 3, 3-9.
  5. Barnes, J. G, 2014. The Fingerprint Sourcebook. 1st ed. UK: Create Space Independent Publishing Platform.
  6. Barton, Iliopoulos, Pissis, C., C. S., S. P., 2014. Fast algorithms for approximate circular string matching. Algorithms for Molecular Biology, 9:9, 10.
  7. Christian, C., Lecroq, T., Handbook of exact string matching algorithms. London, UK:: Kings College Publications, 2004
  8. Colussi, L., 1991. Correctness and efficiency of pattern matching algorithms. Information and Computation, 95, 225251. https://doi.org/10.1016/0890-5401(91)90046-5
  9. Cormen, Leiserson and Rivest, T. H., C. E., and R. L. , 1990. Introduction to Algorithms. 1st ed. Cambridge, Massachusetts: MIT Press.
  10. Dongjae, D.L, 2008. Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on Year: 2008, Volume: 38, Issue: 1. Recognizable-Image Selection for Fingerprint Recognition With a Mobile-Device Camera, 38, Issue 1, 233 243.
  11. Donida, L.R, 2013. Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA), 2013 IEEE International Conference on Year: 2013. Accurate 3D fingerprint virtual environment for biometric technology evaluations and experiment design, http://dx.doi.org/10.1109/CIVEMSA.2013.6617393, 43-48.
  12. Galton, F., 1892. Finger Prints. 1st ed. London, New York: Macmillan and Co. http://www.explainthatstuff.com/. 2004. Biometric fingerprint scanners. [ONLINE] Available at: http://www.explainthatstuff.com/fingerprintscanners.html. [Accessed 31 August 16].
  13. Gao, Q, 2014. A preliminary study of fake fingerprints. I.J Computer Network and Information Security, 12, 1-8.
  14. Landau, Vishkin, G.M., U., 1998. Fast String Matching with k Differences* .Journal of Computer and System Sciences, 37, 63-78. https://doi.org/10.1016/0022-0000(88)90045-1
  15. Merriam-Webster. 2016. Algorithm. [ONLINE] Available at: http://www.merriam-webster.com/dictionary/algorithm. [Accessed 09 September 16].
  16. Miranda, R. C., Ayala-Rinc on, M., Solon, L, 2005. Advances in Bioinformatics and Computational Biology.. 1st ed. Sao Leopoldo, Brazil: Springer Berlin Heidelberg.
  17. Moses, K.R, 2014. The finger print source book. 1st ed. UK: CreateSpace Independent Publishing Platform
  18. Sebastian, S., Literature survey on automated person identification techniques, International Journal of Computer Science and Mobile Computing, vol. 2, no. 5, pp. 232237, 2013
  19. Sheik, S. S., Aggarwal, S. K., Poddar, A., Balakrishnan, N., Sekar, K., 2004. A FAST Pattern Matching Algorithm. J. Chem. Inf. Comput. Sci, 44, 1251-1256. https://doi.org/10.1021/ci030463z
  20. Unar, J., Seng, W. C., and Abbasi, A., A review of biometric technology along with trends and prospects, Pattern Recognition, vol. 47, no. 8, pp. 26732688, 2014 https://doi.org/10.1016/j.patcog.2014.01.016