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Combining Chain-Code and Fourier Descriptors for Fingerprint Matching

  • C. Z. Geevar
  • P. Sojan Lal
Part of the Communications in Computer and Information Science book series (CCIS, volume 192)

Abstract

The performance of an fingerprint recognition system is measured by its accuracy in recognition. For a feature-based fingerprint recognition system, the accuracy is heavily depend on the chosen feature set. A fingerprint image may suffer from problems like translation, rotation, scaling and elastic distortion due to different imaging conditions. A fingerprint recognition algorithm should address these problems before building the feature set. We present a novel method of representing the fingerprint ridge shape as the feature set by combining chain code and fourier descriptor for fingerprint recognition. Experimental results shows that our proposed algorithm is reliable for fingerprint recognition.

Keywords

fingerprint matching chain code fourier descriptors 

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References

  1. 1.
    Biosecure Tool:Performance Evaluation of a Biometric Verification System, http://svnext.it-sudparis.eu/svnview2-eph/ref_syst/Tools/PerformanceEvaluation/
  2. 2.
  3. 3.
    Freeman, H., Davis, L.S.: A corner finding algorithm for chain coded curves. IEEE Transaction in Computing 26, 297–303 (1977)CrossRefGoogle Scholar
  4. 4.
    Geevar, C.Z., Sojan Lal, P.: Reference point estimation in fingerprint image. In: IEEE International Conference on Computational Intelligence and Computing Research (2010)Google Scholar
  5. 5.
    Gonzale, R.C., Wintz, P.: Digital Image Processing. Addison-Wesley, Reading (1987)Google Scholar
  6. 6.
    Jain, A.K., Prabhakara, S., Hong, L., Pankanti, S.: An identity-authentication system using fingerprints. IEEE Trans. Systems Man Cybernet. 85(9), 1365–1388 (1997)Google Scholar
  7. 7.
    Kauppinen, H., Seppanen, T., Pietikainen, M.: An experimental comparison of autoregressive and fourier based descriptors in 2d shape classification. IEEE Transactions on Pattern Analysis and Machine Intelligence 17(2), 201–207 (1995)CrossRefGoogle Scholar
  8. 8.
    Liu, J., Huang, Z., Chan, K.: Direct minutiae extraction from gray-level fingerprint image by relationship examination. In: International Conference on Image Processing, pp. 427–430 (2000)Google Scholar
  9. 9.
    Liu, Y.K., Wei, W., Wang, P.J., Zalik, B.: Compressed vertex chain codes. Pattern Recognition 40(11), 2908–2913 (2007)CrossRefzbMATHGoogle Scholar
  10. 10.
    Madhvanath, S., Kim, G., Govindaraju, V.: Chain code processing for hand-written word recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 21, 928–932 (1997)CrossRefGoogle Scholar
  11. 11.
    Maltoni, D., Maio, D., Jain, A.K., Prabhakar, S.: Handbook of Fingerprint Recognition. Springer, Heidelberg (1991)zbMATHGoogle Scholar
  12. 12.
    Otsu, N.: A threshold selection method from gray-level histogram. IEEE Trans. Systems Man Cybernet. 9, 62–66 (1979)CrossRefGoogle Scholar
  13. 13.
    Persoon, E., Fu, K.: Shape discrimination using fourier descriptors. IEEE Trans. On Systems, Man and Cybernetics SMC-7(3/7), 170–179 (1977)MathSciNetCrossRefGoogle Scholar
  14. 14.
    Rajput, G.G., Horakeria, R., Chandrakant, S.: Printed and handwritten mixed kannada numerals recognition using svm. International Journal on Computer Science and Engineering 2(5), 1622–1626 (2010)Google Scholar
  15. 15.
    Siddiqi, I., Vincent, N.: A set of chain code based features for writer recognition. In: Proceedings of the 10th International Conference on Document Analysis and Recognition (2009)Google Scholar
  16. 16.
    Smach, F., Lematre, C., Gauthier, J.-P., Miteran, J., Atri, M.: Generalized fourier descriptors with applications to objects recognition in svm context. Journal of Mathematical Vision and Imaging 30(1), 43–71 (2006)MathSciNetCrossRefGoogle Scholar
  17. 17.
    Zhang, D., Lu, G.: A comparative study of fourier descriptors for shape representation and retrieval. In: The 5th Asian Conference on Computer Vision, pp. 23–25 (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • C. Z. Geevar
    • 1
    • 2
  • P. Sojan Lal
    • 1
    • 2
  1. 1.Department of Computer ApplicationMES College of EngineeringKuttippuramIndia
  2. 2.School of Computer ScienceMahatma Gandhi UniversityKottayamIndia

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