Fingerprint Enhancement Using Circular Gabor Filter

  • En Zhu
  • Jianping Yin
  • Guomin Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3212)


Fingerprint minutiae are prevalently used in AFISs. The extraction of fingerprint minutiae is heavily affected by the quality of fingerprint images. This leads to the incorporation of a fingerprint enhancement module in AFIS to make the system robust with respect to the quality of input fingerprint images. Most of existing enhancement methods suffer from mainly two kinds of defects: (1) time consuming and thus unusable in time critical applications; and (2) blocky effect in the enhanced image. This paper follows Hong’s Gabor filter based enhancement scheme (IEEE Trans. PAMI, vol.20, no.8, pp. 777-789, 1998) but uses a circle support filter and tunes the filter’s frequency and size differently. This scheme can enhance the fingerprint image rapidly and overcome the blocky effect effectively and does improve the performance of minutiae detection.


Average Frequency Gabor Filter Fingerprint Image Enhancement Scheme Time Critical Application 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Hong, L., Jain, A., Pankati, S., Bolle, R.: Fingerprint Enhancement. In: Proc. IEEE Workshop on Applications of Computer Vision, Sarasota, Fl, December 1996, pp. 202–207 (1996)Google Scholar
  2. 2.
    Greenberg, S., Aladjem, M., Kogan, D., Dimitrov, I.: Fingerprint Image Enhancement Using Filtering Techniques. In: International Conference on Pattern Recognition (ICPR 2000), September 2000, vol. 3 (2000)Google Scholar
  3. 3.
    Simon-Zorita, D., Ortega-Garcia, J., Cruz-Llanas, S., Sanchez-Bote, J.L., Glez- Rodriguez, J.: An Improved Image Enhancement Scheme for Fingerprint Minutiae Extraction in Biometric Identification. In: Proceedings of the Third Audio and Video-Based Person Authentication, Halmstad, Sweden (June 2001)Google Scholar
  4. 4.
    Hong, L., Wang, Y., Jain, A.: Fingerprint Image Enhancement: Algorithm and Performance Evaluation. IEEE Transactions on Pattern Analysis and Machine Intelligence 20(8), 777–789 (1998)CrossRefGoogle Scholar
  5. 5.
    Sasakawa, K., Isogai, F., Ikebata, S.: Personal verification system with high tolerance of poor quality fingerprint. In: Proc. SPIE, vol. 1386, pp. 265–272 (1990)Google Scholar
  6. 6.
    Mehtre, B.M.: Fingerprint image analysis for automatic identification. Machine Vision and Applications 6, 124–139 (1993)CrossRefGoogle Scholar
  7. 7.
    Bergengruen, O.: Preprocessing of poor quality fingerprint images. In: XIV intl. Conf. of the Chilean Computer Science Society (October 1994)Google Scholar
  8. 8.
    Karu, K., Jain, A.K.: Fingerprint Classification. Pattern Recognition 29(3), 389–404 (1996)CrossRefGoogle Scholar
  9. 9.
    Bazen, A.M., Gerez, S.H.: Systematic Methods for the Computation of the Directional Fields and Singular Points of Fingerprints. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(7), 905–919 (2002)CrossRefGoogle Scholar
  10. 10.
    Maio, Maltoni: Direct gray-scale minutiae detection in finger-prints. IEEE Trans. Pattern Anal. Machine Intell. 19(1), 27–39 (1997)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • En Zhu
    • 1
  • Jianping Yin
    • 1
  • Guomin Zhang
    • 1
  1. 1.School of Computer ScienceNational University of Defense TechnologyChangshaChina

Personalised recommendations