Skip to main content
SpringerLink
Log in

On Adaptive Fingerprint Pore Extraction

  • Conference paper
Image Analysis and Recognition (ICIAR 2013)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7950))

Included in the following conference series:

Abstract

Pore extraction appears to play an important role in latent (or fragmentary) fingerprint examination and in applications involving large population or high security levels. In this paper, we introduce a novel pore extraction approach designed to deal with anisotropic fingerprint aspects, which can be used to detect both closed and open pores. The method combines the directional field information with a toggle mapping to estimate fingerprint ridges location. It has proved to be very robust to noise and, as we will show through some experiments, it outperforms well-known state-of-the-art methods. Although we illustrate its application only on a specific database, our approach is quite general, simple and can be easily extended to others image applications involving similar feature extraction.

This work has been supported by Brazilian agencies CAPES, CNPq and FAPESP.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Rotationally invariant statistics for examining the evidence from the pores in fingerprints. Law, Probability and Risk  7, 1 – 4 (2008)

    Google Scholar 

  2. Dorini, L.B., Leite, N.J.: A scale-space toggle operator for morphological segmentation. In: Proceedings of 8th Int. Symp. on Mathematical Morphology, vol. 1, pp. 101–112 (2007)

    Google Scholar 

  3. Feng, J., Jain, A.K.: Fingerprint reconstruction: from minutiae to phase. IEEE Transactions on Pattern Analysis and Machine Intelligence 33, 209–223 (2011)

    Article  Google Scholar 

  4. Gu, J., Zhou, J., Zhang, D.: A combination model for orientation field of fingerprints. Pattern Recognition 37(3), 543–553 (2004)

    Article  Google Scholar 

  5. Jackway, P.T., Deriche, M.: Scale-space properties of the multiscale morphological dilation-erosion. IEEE Transactions on Pattern Analysis and Machine Intelligence 18(1), 38–51 (1996)

    Article  Google Scholar 

  6. Jain, A.K., Chen, Y., Demirkus, M.: Pores and ridges: fingerprint matching using level 3 features. IEEE Trans. Pattern Anal. Mach. Intell. 29, 15–27 (2007)

    Article  Google Scholar 

  7. Jain, A.K., Prabhakar, S., Hong, L., Pankanti, S.: Filterbank-based fingerprint matching. IEEE Trans. Image Process 9(5), 846–859 (2004)

    Article  Google Scholar 

  8. Maio, D., Maltoni, D., Cappelli, R., Wayman, J., Jain, A.: Fvc2002: Second fingerprint verification competition. In: Proceedings of 16th International Conference on Pattern Recognition, vol. 3, pp. 811–814 (2002)

    Google Scholar 

  9. Maltoni, D., Maio, D., Jain, A.K., Prabhakar, S.: Handbook of Fingerprint Recognition, 2nd edn. Springer (2009)

    Google Scholar 

  10. Marr, D.: Vision: A Computational Investigation into the Human Representation and Processing of Visual Information. Henry Holt and Co., Inc., New York (1982)

    Google Scholar 

  11. O’Gorman, L., Nickerson, J.V.: An approach to fingerprint filter design. Pattern Recognition 22(1), 29–38 (1989)

    Article  Google Scholar 

  12. Oliveira, M.A., Leite, N.J.: A multiscale directional operator and morphological tools for reconnecting broken ridges in fingerprint images. Pattern Recognition 41(1), 367–377 (2008)

    Article  MATH  Google Scholar 

  13. Rao, A., Jain, R.: Computerized flow field analysis: oriented texture fields. IEEE Transactions on Pattern Analysis and Machine Intelligence 14(7), 693–709 (1992)

    Article  Google Scholar 

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

    Article  Google Scholar 

  15. Serra, J., Vincent, L.: An overview of morphological filtering. Circuits, Systems, and Signal Processing 11(1), 47–108 (1992)

    Article  MathSciNet  MATH  Google Scholar 

  16. Soille, P.: Morphological Image Analysis. Springer (1999)

    Google Scholar 

  17. Zhao, Q., Zhang, D., Zhang, L., Luo, N.: Adaptive fingerprint pore modeling and extraction. Pattern Recognition 43(8), 2833–2844 (2010)

    Article  MATH  Google Scholar 

  18. Zhao, Q., Zhang, D., Zhang, L., Luo, N.: High resolution partial fingerprint alignment using pore-valley descriptors. Pattern Recognition 43(3), 1050–1061 (2010)

    Article  MATH  Google Scholar 

  19. Zhou, J., Chen, F., Gu, J.: A novel algorithm for detecting singular points from fingerprint images. IEEE Trans. Pattern Anal. Mach. Intell. 31, 1239–1250 (2009)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Computing, University of Campinas, Av. Albert Einstein, 1251 - Barão Geraldo, Campinas, SP, CEP: 13083-852, Brazil

    Raoni Florentino da Silva Teixeira & Neucimar Jerônimo Leite

Authors
  1. Raoni Florentino da Silva Teixeira
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Neucimar Jerônimo Leite
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Waterloo, 200 University Avenue West, N2L 3G1, Waterloo, ON, Canada

    Mohamed Kamel

  2. Faculty of Engineering, Institute of Biomedical Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    Aurélio Campilho

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

da Silva Teixeira, R.F., Leite, N.J. (2013). On Adaptive Fingerprint Pore Extraction. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2013. Lecture Notes in Computer Science, vol 7950. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39094-4_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-39094-4_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39093-7

  • Online ISBN: 978-3-642-39094-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation