Spatial Relation Approach to Fingerprint Matching

  • Gabriel Babatunde Iwasokun
  • Oluwole Charles Akinyokun
  • Cleopas Officer Angaye
Part of the Studies in Computational Intelligence book series (SCI, volume 542)

Abstract

This paper presents the formulation and implementation of a new fingerprint pattern-matching algorithm. The algorithm uses the spatial relation between the junction points within the 11 x 11 neighbourhood of the core points to generate the pattern matching scores. The junction points were the points of intersections of straight lines connecting the feature points within the neighbourhood. Experiments were conducted using FVC2002 fingerprint database comprising four datasets of images of different sources and qualities. Three statistics; namely False acceptance rate (FAR), False rejection rate (FRR) and the Average Matching Time (AMT) were generated for measuring the performance of the algorithm on the images. The results obtained demonstrated the effectiveness of the algorithm in distinguishing fingerprint images from different fingers. The results also revealed the failure rate of the algorithm when subjected to images with regions of significant degradations. Finally, findings from comparative analysis of the generated results with what obtained for some recently formulated fingerprint pattern matching algorithms revealed best performance for the proposed algorithm.

Keywords

Fingerprint matching minutiae spatial relation FRR FAR 

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References

  1. 1.
    Eckert, W.G.: Introduction to Forensic Science. Elsevier, New York (1996)Google Scholar
  2. 2.
    FIDIS. Future of Identity in the Information Society. Elsvier Inc. (2006)Google Scholar
  3. 3.
    Salter, D.: Thumbprint – An Emerging Technology, Engineering Technology, New Mexico State University (2006)Google Scholar
  4. 4.
    Wayman, J., Maltoni, D., Jain, A., Maio, D.: Biometric Systems. Springer-Verlag London Limited (2005)Google Scholar
  5. 5.
    Akinyokun, O.C., Adegbeyeni, E.O.: Scientific Evaluation of the Process of Scanning and Forensic Analysis of Thumbprints on Ballot Papers. In: Proceedings of Academy of Legal, Ethical and Regulatory Issues, New Orleans, vol. 13(1) (2009)Google Scholar
  6. 6.
    Yount, L.: Forensic Science: From Fibres to Thumbprints. Chelsea House Publisher (2007)Google Scholar
  7. 7.
    Michael, C., Imwinkelried, E.: A Cautionary Note about Fingerprint Analysis and Reliance on Digital Technology. Public Defence Backup Center REPOR, vol. XXI(3T), pp. 7–9 (2006)Google Scholar
  8. 8.
    Nanavati, S., Thieme, M., Nanavati, R.: Biometrics, Identifying Verification in a Networked World, pp. 15–40. John Wiley & Sons, Inc. (2002)Google Scholar
  9. 9.
    Anil, K.J., Jianjiang, F., Karthik, N.: Fingerprint Matching, pp. 36–44. IEEE Computer Society (2010)Google Scholar
  10. 10.
    McMurray, H.N., Williams, G.: Latent Thumb Mark Visualization Using a Scanning Kelvin Probe. Forensic Science International (2007)Google Scholar
  11. 11.
  12. 12.
    Iwasokun, G.B., Akinyokun, O.C., Alese, B.K., Olabode, O.: A Modified Approach to Crossing Number and Post-Processing Algorithms for Fingerprint Minutiae Extraction and Validation. IMS Manthan International Journal of Computer Science and Technology 6(1), 1–9 (2011)Google Scholar
  13. 13.
    Shenglin, Y., Ingrid, M.V.: A Secure Fingerprint Matching Technique (2003), www.cosic.esat.kuleuban.be/publications/article-723.pdf (accessed January 23, 2012)
  14. 14.
    Jianjiang, F.: Combining minutiae descriptors for fingerprint matching. Elsevier Pattern Recognition 41, 342–352 (2008)Google Scholar
  15. 15.
    Anil, K.J., Jianjiang, F.: Latent Fingerprint Matching. IEEE Transactions on Pattern Analysis and Machine Intelligence 33(1), 88–100 (2011)Google Scholar
  16. 16.
    He, Y., Tian, J., Member, S., Li, L., Chen, H., Yang, X.: Fingerprint Matching Based on Global Comprehensive Similarity (2005), http://www.fingerpass.net/downloads/papers/Fingerprint%20Matching%20Based%20on%20Global%20Comprehensive%20Similarity.pdf (accessed August 21, 2012)
  17. 17.
    Jain, A.K., Prabhakar, S., Hong, L., Pankanti, S.: Filterbank-Based Fingerprint Matching. IEEE Transactions on Image Processing 9(5) (2000)Google Scholar
  18. 18.
    Jain, A.K., Hong, L., Pankanti, S., Bolle, R.: An identity authentication system using fingerprints. Proc. IEEE 85(9), 1365–1388 (1997)Google Scholar
  19. 19.
    Giuseppe, P.E., Albert, N.: Fingerprint Matching Using Minutiae Triangulation (2003), http://idisk.mac.com/geppy.parziale/Public/Papers/delaunay.pdf (accessed January 23, 2012)
  20. 20.
    Xinjian, C., Jie, T., Xin, Y., Yangyang, Z.: An Algorithm for Distorted Fingerprint Matching Based on Local Triangle Feature Set. IEEE Transactions on Information Forensics and Security 1(2), 169–177 (2006)Google Scholar
  21. 21.
    Raymond, T.: Fingerprint Image Enhancement and Minutiae Extraction, PhD Thesis Submitted to School of Computer Science and Software Engineering, University of Western Australia, pp. 21–56 (2003)Google Scholar
  22. 22.
    Hong, L., Wau, Y., Anil, J.: Fingerprint image enhancement: Algorithm and performance evaluation. In: Pattern Recognition and Image Processing Laboratory, Department of Computer Science, Michigan State University, pp. 1–30 (2006)Google Scholar
  23. 23.
    Iwasokun, G.B., Akinyokun, O.C., Alese, B.K., Olabode, O.: Fingerprint Image Enhancement: Segmentation to Thinning. International Journal of Advanced Computer Science and Applications (IJACSA) 3(1) (2012)Google Scholar
  24. 24.
    Iwasokun, G.B., Akinyokun, O.C., Alese, B.K., Olabode, O.: Adaptive and Faster Approach to Fingerprint Minutiae Extraction and Validation. International Journal of Computer Science and Security 5(4), 414–424 (2011)Google Scholar
  25. 25.
    López, A.C., Ricardo, R.L., Queeman, R.C.: Fingerprint Pattern Recognition, PhD Thesis, Electrical Engineering Department, Polytechnic University (2002)Google Scholar
  26. 26.
    Iwasokun, G.B., Akinyokun, O.C., Olabode, O.: A Mathematical Modeling Approach to Fingerprint Ridge Segmentation and Normalization. International Journal of Computer Science and Information Technology & Security 2(2), 263–267 (2012)Google Scholar
  27. 27.
    Iwasokun, G.B., Akinyokun, O.C., Olabode, O.: A Block Processing Approach to Fingerprint Ridge Orientation Estimation. Journal of Computer Technology and Application 3, 401–407 (2012)Google Scholar
  28. 28.
    Hong, L., Wau, Y., Anil, J.: Fingerprint image enhancement: Algorithm and performance evaluation. In: Pattern Recognition and Image Processing Laboratory, Department of Computer Science, Michigan State University, pp. 1–30 (2006)Google Scholar
  29. 29.
    Navrit, K.J., Amit, K.: A Novel Method for Fingerprint Core Point Detection. International Journal of Scientific & Engineering Research 2(4), 1–6 (2011)Google Scholar
  30. 30.
    Maio, D., Maltoni, D., Cappelli, R., Wayman, J.L., Jain, A.K.: FVC2002: Second Fingerprint Verification Competition. In: 16th International Conference on Pattern Recognition 2002, pp. 811–814 (2002)Google Scholar
  31. 31.
    Li, T., Liang, C., Sei-ichiro, K.: Fingerprint Matching Using Dual Hilbert Scans. In: SITIS, pp. 553–559 (2009)Google Scholar
  32. 32.
    Jain, A.K., Prabhakar, S., Chen, S.: Combining multiple matchers for a high security Fingerprint verification system. Pattern Recognition Letters 20, 1371–1379 (1999)CrossRefGoogle Scholar
  33. 33.
    Nandakumar, K.: A Fingerprint Cryptosystem Based on Minutiae Phase Spectrum. In: WIFS 2010, USA (2010)Google Scholar
  34. 34.
    Perez-Diaz, A.J., Arronte-Lopez, I.C.: Fingerprint Matching and Non-Matching Analysis for Different Tolerance Rotation Degrees in Commercial Matching Algorithms. Journal of Applied Research and Technology 8(2), 186–199 (2010)Google Scholar
  35. 35.
    Peer, P.: Fingerprint-Based Verification System A Research Prototype. In: IWSSIP 2010 - 17th International Conference on Systems, Signals and Image Processing, pp. 150–153 (2010)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Gabriel Babatunde Iwasokun
    • 1
  • Oluwole Charles Akinyokun
    • 1
  • Cleopas Officer Angaye
    • 2
  1. 1.Department of Computer ScienceFederal University of TechnologyAkureNigeria
  2. 2.National Information Technology Development AgencyAbujaNigeria

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