Fingerprint Image Enhancement Using STFT Analysis

  • Sharat Chikkerur
  • Venu Govindaraju
  • Alexander N. Cartwright
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3687)

Abstract

Contrary to popular belief, despite decades of research in fingerprints, reliable fingerprint recognition is still an open problem. Extracting features out of poor quality prints is the most challenging problem faced in this area. This paper introduces a new approach for fingerprint enhancement based on Short Time Fourier Transform(STFT) Analysis. STFT is a well known technique in signal processing to analyze non-stationary signals. Here we extend its application to 2D fingerprint images.The algorithm simultaneously estimates all the intrinsic properties of the fingerprints such as the foreground region mask, local ridge orientation and local frequency orientation. We have evaluated the algorithm over a set of 800 images from FVC2002 DB3 database and obtained a 17% relative improvement in the recognition rate.

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References

  1. 1.
    Maio, D., Maltoni, D., Jain, A.K., Prabhakar, S.: Handbook of Fingerprint Recognition. Springer, Heidelberg (2003)MATHGoogle Scholar
  2. 2.
    O’Gormann, L., Nickerson, J.V.: An approach to fingerprint filter design. Pattern Recognition 22, 29–38 (1989)CrossRefGoogle Scholar
  3. 3.
    Greenberg, S., Aladjem, M., Kogan, D., Dimitrov, I.: Fingerprint image enhancement using filtering techniques. In: International Conference on Pattern Recognition, vol. 3, pp. 326–329 (2000)Google Scholar
  4. 4.
    Yang, G.Z., Burger, P., Firmin, D.N., Underwood, S.R.: Structure adaptive anisotropic image filtering. Image and Vision Computing 14, 135–145 (1996)CrossRefGoogle Scholar
  5. 5.
    Hong, L., Wang, Y., Jain, A.K.: Fingerprint image enhancement: Algorithm and performance evaluation. Transactions on PAMI 21, 777–789 (1998)Google Scholar
  6. 6.
    Qian, S., Chen, D.: Joint Time-Frequency Analysis, Methods and Applications. Prentice-Hall, Englewood Cliffs (1996)Google Scholar
  7. 7.
    Sherlock, B.G., Monro, D.M., Millard, K.: Fingerprint enhancement by directional fourier filtering. Visual Image Signal Processing 141, 87–94 (1994)CrossRefGoogle Scholar
  8. 8.
    Connell, J., Ratha, N.K., Bolle, R.M.: Fingerprint image enhancement using weak models. In: IEEE International Conference on Image Processing (2002)Google Scholar
  9. 9.
    Srinivasan, V.S., Murthy, N.N.: Detection of singular points in fingerprint images. Pattern Recognition 25, 139–153 (1992)CrossRefGoogle Scholar
  10. 10.
    Bazen, A.M., Gerez, S.: Extraction of singular points from directional fields of fingerprints (2001)Google Scholar
  11. 11.
    Kawagoe, M., Tojo, A.: Fingerprint pattern classification. Pattern Recogntion 17, 295–303 (1987)CrossRefGoogle Scholar
  12. 12.
    Mehtre, B.M., Murthy, N.N., Kapoor, S., Chatterjee, B.: Segmentation of fingerprint images using the directional image. Pattern Recognition 20, 429–425 (1987)Google Scholar
  13. 13.
    Cappelli, R., Lumini, A., Maio, D., Maltoni, D.: Fingerprint classification by directional image partitioning. IEEE Transactions on Pattern Analysis and Machine Intelligence  21 (1999)Google Scholar
  14. 14.
    Candela, G.T., Grother, P.J., Watson, C.I., Wilkinson, R.A., Wilson, C.L.: Pcasys - a patternlevel classification automation system for fingerprints (1995)Google Scholar
  15. 15.
    Karu, K., Jain, A.: Fingerprint classification (1996)Google Scholar
  16. 16.
    Rao, K., Balck, K.: Type classification of fingerprints: A syntactic approach. IEEE Transactions on Pattern Analysis and Machine Intelligence 2, 223–231 (1980)CrossRefGoogle Scholar
  17. 17.
    Jain, A.K., Prabhakar, S., Hong, L.: A multichannel approach to fingerprint classification. IEEE Transactions on Pattern Analysis and Machine Intelligence 21, 348–359 (1999)CrossRefGoogle Scholar
  18. 18.
    Gonzalez, Woods, Eddins: Digital Image Processing. Prentice Hall, Englewood Cliffs (2004)Google Scholar
  19. 19.
    Kaas, M., Witkin, A.: Analyzing oriented patterns. Computer Vision Graphics Image Processing 37, 362–385 (1987)CrossRefGoogle Scholar
  20. 20.
    Maio, D., Maltoni, D.: Neural network based minutiae filtering in fingerprint images. In: 14th International Conference on Pattern Recognition., pp. 1654–1658 (1998)Google Scholar
  21. 21.
    Haykin, S., Veen, B.V.: Signals and Systems. John Wiley and Sons, Chichester (1999)MATHGoogle Scholar
  22. 22.
    Rabiner, Schafer: Digital Processing of Speech Signals. Prentice Hall International, Englewood Cliffs (1978)Google Scholar
  23. 23.
    Sonka, Hlavac, Boyle: Image Processing, Analysis and Machine Vision, 2nd edn. Thomson, Asia (2004)Google Scholar
  24. 24.
    Rao, A.R.: A Taxonomy of Texture Descriptions. Springer, HeidelbergGoogle Scholar
  25. 25.
    (Fingerprint verification competition), http://bias.csr.unibo.it/fvc2002/

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Sharat Chikkerur
    • 1
  • Venu Govindaraju
    • 1
  • Alexander N. Cartwright
    • 1
  1. 1.Center for Unified Biometrics and SensorsUniversity at BuffaloUSA

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