Skip to main content

Fingerprint Image Enhancement Using Steerable Filter in Wavelet Domain

  • Conference paper
  • First Online:
Intelligent Systems Design and Applications (ISDA 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 736))

  • 1805 Accesses

Abstract

The proposed work is to enhance the features of the fingerprint image using steerable filter in wavelet domain to increase the accuracy and speed of Automatic fingerprint identification system. The proposed method uses steerable filter and wavelet. The steerable filter allows filtering process adaptively to any orientation and determining analytically the filter output as a function of orientation and the wavelet domain speeds up the computation process. The steerable filter is applied on each local blocks of approximation image of wavelet transform for tuning up the fingerprint image features and then smoothing the resultant which leads to enhanced image. Experiments are conducted on FVC databases and results show that enhancement process reveals clear visualization of fingerprint images.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Blotta, E., Moler, E.: Fingerprint image enhancement by differential hysteresis processing. Forensic Sci. Int. 141(2), 109–113 (2004)

    Article  Google Scholar 

  2. Cavusoglu, A., Gorgunoglu, S.: A fast fingerprint image enhancement algorithm using a parabolic mask. Comput. Electr. Eng. 34(3), 250–256 (2008)

    Article  MATH  Google Scholar 

  3. Cheng, J., Tian, J.: Fingerprint enhancement with dyadic scale-space. Pattern Recognit. Lett. 25(11), 1273–1284 (2004)

    Article  Google Scholar 

  4. Chikkerur, S., Cartwright, A.N., Govindaraju, V.: Fingerprint enhancement using STFT analysis. Pattern Recognit. 40(1), 198–211 (2007)

    Article  MATH  Google Scholar 

  5. Feng, X.G., Milanfar, P.: Multiscale principal components analysis for image local orientation estimation. IEEE Signals Syst. Comput. 1, 478–482 (2002)

    Google Scholar 

  6. Freeman, W.T., Adelson, E.H.: The design and use of steerable filter. IEEE Trans. Pattern Anal. Mach. Intell. 13(9), 891–906 (1991)

    Article  Google Scholar 

  7. Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 3rd edn, p. 717. Pearson Education India, New Jersey (2009). Image Analysis

    Google Scholar 

  8. Gottschlich, C.: Curved-region-based ridge frequency estimation and curved Gabor filters for fingerprint image enhancement. IEEE Trans. Image Process. 21(4), 2220–2227 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  9. Hong, L., Wan, Y., Jain, A.: Fingerprint image enhancement: algorithm and performance evaluation. IEEE Trans. Pattern Anal. Mach. Intell. 20(8), 777–789 (1998)

    Article  Google Scholar 

  10. Hsieh, C.-T., Lai, E., Wang, Y.-C.: An effective algorithm for fingerprint image enhancement based on wavelet transform. Pattern Recognit. 36(2), 303–312 (2003)

    Article  Google Scholar 

  11. Yang, J., Liu, L., Jiang, T., Fan, Y.: A modified Gabor filter design method for fingerprint image enhancement. Pattern Recognit. Lett. 24(12), 1805–1817 (2003)

    Article  Google Scholar 

  12. Maltoni, D., Maio, D., Jain, A., Prabhakar, S.: Handbook of Fingerprint Recognition, p. 103. Springer Science & Business Media, London (2009)

    Book  MATH  Google Scholar 

  13. Paul, A.M., Lourde, R.M.: A study on image enhancement techniques for fingerprint identification. In: IEEE International Conference on Video and Signal Based Surveillance, p. 16 (2006)

    Google Scholar 

  14. Ratha, N.K., Chen, S., Jain, A.K.: Adaptive flow orientation-based feature extraction in fingerprint image. Pattern Recognit. 28(11), 1657–1672 (1995)

    Article  Google Scholar 

  15. Shi, Z., Govindaraju, V.: A chaincode based scheme for fingerprint feature extraction. Pattern Recogni. Lett. 27(5), 462–468 (2006)

    Article  Google Scholar 

  16. Wang, W., Li, J., Huang, F., Feng, H.: Design and implementation of Log-Gabor filter in fingerprint image enhancement. Pattern Recognit. Lett. 29(3), 301–308 (2008)

    Article  Google Scholar 

  17. Wu, C., Tulyakov, S., Govindaraju, V.: Robust point-based feature fingerprint segmentation algorithm. In: Lee, S.-W., Li, S.Z. (eds.) International Conference on Biometrics. LNCS, vol. 4642, pp. 1095–1103. Springer, Heidelberg (2007)

    Google Scholar 

  18. Wu, C., Shi, Z., Govindaraju, V.: Fingerprint image enhancement method using directional median filter. In: Proceedings of SPIE, vol. 5404, p. 67 (2004)

    Google Scholar 

  19. Yang, J., Liu, L., Jiang, T., Fan, Y.: An effective algorithm for fingerprint image enhancement based on wavelet transform. Pattern Recognit. 36(2), 303–312 (2003)

    Article  Google Scholar 

  20. Yang, J., Xiong, N., Vasilakos, A.V.: Two-stage enhancement scheme for low quality fingerprint images by learning from the images. IEEE Trans. Hum. Mach. Syst. 43(2), 235–248 (2013)

    Article  Google Scholar 

  21. Ye, Q., Xiang, M., Cui, Z.: Fingerprint image enhancement algorithm based on two dimension EMD and Gabor filter. Procedia Eng. 29, 1840–1844 (2012)

    Article  Google Scholar 

  22. Zhang, W., Tang, Y.Y., You, X.: Fingerprint enhancement using wavelet transform combined with Gabor filter. Int. J. Pattern Recognit. Artif. Intell. 18(8), 1391–1406 (2004)

    Article  Google Scholar 

  23. FVC2000 Set B Databases. http://bias.csr.unibo.it/fvc2000/download.asp

  24. FVC2002 Set B Databases. http://bias.csr.unibo.it/fvc2002/download.asp

  25. FVC2004 Set B Databases. http://bias.csr.unibo.it/fvc2004/download.asp

Download references

Acknowledgement

This work is funded by University Grants Commission Major Research Project (MRP: F.No. 42-144/2013(SR)), New Delhi, INDIA

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to T. Kathirvalavakumar .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Jeyalakshmi, K.S., Kathirvalavakumar, T. (2018). Fingerprint Image Enhancement Using Steerable Filter in Wavelet Domain. In: Abraham, A., Muhuri, P., Muda, A., Gandhi, N. (eds) Intelligent Systems Design and Applications. ISDA 2017. Advances in Intelligent Systems and Computing, vol 736. Springer, Cham. https://doi.org/10.1007/978-3-319-76348-4_31

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-76348-4_31

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-76347-7

  • Online ISBN: 978-3-319-76348-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics