Advertisement

A Novel Fingerprint Enhancement Algorithm Using Curve Mask

  • Xuzhou Li
  • Liming Zhang
  • Yilong Yin
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 321)

Abstract

Fingerprint image enhancement is an essential preprocessing step in fingerprint recognition applications. In this paper, a Separable Gabor filter with Bresenham (SGB) is introduced for fast fingerprint enhancement. A Curve Mask Gabor (CMG) is designed to improve the performance of SGB. Experiments are performed on FVC2004. Results indicate that the SGB can significantly reduce computational complexity, and the CMG is also faster than traditional 2-D Gabor enhancement. Moreover, the CMG can improve the enhancement performance of SGB, and obtain better enhanced images, especially in pattern and noisy areas.

Keywords

fingerprint enhancement Gabor Bresenham curve mask 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Daugman, J.: Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two dimensional visual cortical filters. Journal of the Optical Society of America A: Optics, Image Science & Vision (JOSA A) 2(7), 1160–1169 (1985)CrossRefGoogle Scholar
  2. 2.
    Daugman, J.G.: Complete discrete 2D Gabor transforms by neural networks for image analysis and compression. IEEE Transactions on Acoustics, Speech and Signal P (ASASP) 16(7), 1169–1179 (1988)CrossRefGoogle Scholar
  3. 3.
    Hong, L., Wan, 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
  4. 4.
    Yang, J.W., Liu, L.F.: A modified Gabor filter design method for fingerprint image enhancement. Pattern Recognition Letters, 1805–1817 (2003)Google Scholar
  5. 5.
    Greenberg, S., Aladjem, M., Kogan, D.: Fingerprint Image Enhancement Using Filtering Techniques. Real-Time Imaging 8, 227–236 (2002)zbMATHCrossRefGoogle Scholar
  6. 6.
    Areekul, V., Watchareeruetai, U., Tantaratana, S.: Fast Separable Gabor Filter for Fingerprint Enhancement. In: Proceeding of International Conference on Biometric Authentication (ICBA) 2004, pp. 403–409 (2004)Google Scholar
  7. 7.
    Areekul, V., Tantararana, S.: Separable Gabor Filter Realization for Fast Fingerprint Enhancement. In: Proceeding of IEEE International Conference on ICIP, vol. 3, pp. III.253–III.256 (2005)Google Scholar
  8. 8.
    Wang, W., Li, J.W., Huang, F.F., Feng, H.L.: Design and implementation of Log-Gabor filter in fingerprint image enhancement. Pattern Recognition Letters 29, 301–308 (2008)zbMATHCrossRefGoogle Scholar
  9. 9.
    Kovacs-Vajna, Z.M., Rovatti, R., Frazzoni, M.: Fingerprint ridge distance computation methodologies. Pattern Recognition 33, 69–80 (2000)CrossRefGoogle Scholar
  10. 10.
    Yin, Y.L., Zhan, X.S.: An Algorithm Based on Gabor Function for Fingerprint Enhancement and Its Application. Journal of Software 14(3), 484–489 (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Xuzhou Li
    • 1
    • 2
  • Liming Zhang
    • 1
  • Yilong Yin
    • 1
  1. 1.School of Computer Science and TechnologyShandong UniversityJinanChina
  2. 2.Shandong Youth University of Political ScienceJinanChina

Personalised recommendations