Skip to main content
SpringerLink
Log in

Multi-constrained Orientation Field Modeling and Its Application for Fingerprint Indexing

  • Conference paper
  • First Online:
Network and System Security (NSS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 9408))

Included in the following conference series:

Abstract

Fingerprint orientation field, representing the fingerprint ridge-valley structure direction, plays an essential role in fingerprint preprocessing tasks. Orientation field is able to be reconstructed by either non-parameterized or parameterized methods. In this paper, we propose a new parameterized approach for orientation field modeling. The proposed algorithm minimizes a composite model including three constraints corresponding to a least square data fitting term, a total variation regularization and a \(L_1\) sparse regularization. This model has been shown to be very effective for fingerprint orientation field reconstruction. Furthermore, its effectiveness has been proven by several experiments. First, the experiments on poor-quality fingerprint images are conducted. Visual comparisons demonstrate the robustness of the proposed method when processing noisy fingerprint images. Then, as another application of the proposed model, its resultant sparse representation is employed for fingerprint indexing. The experiments on FVC 2000 DB2a and FVC 2002 DB1a datasets show the superior performance of the proposed model for fingerprint indexing.

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. Hong, L., Wan, Y., Jain, A.K.: Fingerprint image enhancement algorithm and performance evaluation. IEEE Transactions on Pattern Analysis and Machine Intelligence 20(8), 777–789 (1998)

    Article  Google Scholar 

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

    Article  MATH  Google Scholar 

  3. Wang, Y., Hu, J., Phillips, D.: A fingerprint orientation model based on 2D fourier expansion (FOMFE) and its application to singular point detection and fingerprint indexing. IEEE Transactions on Pattern Analysis and Machine Intelligence 29(4), 573–585 (2007)

    Article  Google Scholar 

  4. Wang, Y., Hu, J.: Global ridge orientation modelling for partial fingerprint identification. IEEE Transactions on Pattern Analysis and Machine Intelligence 33(1), 72–87 (2011)

    Article  Google Scholar 

  5. Zhou, W., Hu, J., Petersen, I., Bennamoun, M.: Partial fingerprint reconstruction with improved smooth extension. In: Lopez, J., Huang, X., Sandhu, R. (eds.) NSS 2013. LNCS, vol. 7873, pp. 756–762. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  6. Feng, J., Zhou, J., Jain, A.K.: Orientation field estimation for latent fingerprint enhancement. IEEE Transactions on Pattern Analysis and Machine Intelligence 35(4), 925–940 (2013)

    Article  Google Scholar 

  7. Ram, S., Bischof, H., Birchbauer, J.: Modeling fingerprint ridge orientation using Legendre polynomials. Pattern Recognition 43(1), 342–357 (2010)

    Article  MATH  Google Scholar 

  8. Liu, M., Yap, P.T.: Invariant representation of orientation fields for fingerprint indexing. Pattern Recognition 45(7), 2532–2542 (2012)

    Article  Google Scholar 

  9. Liu, M., Liu, S., Zhao, Q.: Fingerprint orientation field reconstruction by weighted discrete cosine transform. Information Sciences 268, 65–77 (2014)

    Article  Google Scholar 

  10. Maltoni, D., Maio, D., Jain, A.K., Prabhakar, S.: Hand book of fingerprint recognition. Springer Verlag (2009)

    Google Scholar 

  11. Tropp, J.: Greed is good: Algorithmic results for sparse approximation. IEEE Transactions on Information Theory 50(10), 2231–2242 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  12. Zhou, J., Gu, J.: A model-based method for the computation of fingerprints’ orientation field. IEEE Transactions on Image Processing 13(6), 821–835 (2004)

    Article  Google Scholar 

  13. Wang, Y., Hu, J., Han, F.: Enhanced gradient-based algorithm for the estimation of fingerprint orientation fields. Applied Mathematics and Computation 185, 823–833 (2007)

    Article  MATH  Google Scholar 

  14. Zhou, W., Hu, J., Wang, S., Petersen, I., Bennamoun, M.: Fingerprint indexing based on combination of novel minutiae triplet features. In: Au, M.H., Carminati, B., Kuo, C.-C.J. (eds.) NSS 2014. LNCS, vol. 8792, pp. 377–388. Springer, Heidelberg (2014)

    Google Scholar 

  15. Huang, J., Zhang, S., Metaxas, D.: Efficient MR image reconstruction for compressed MR images. Medical Image Analysis 15, 670–679 (2011)

    Article  Google Scholar 

  16. Amir, B., Marc, T.: Fast gradient-based algorithms for constrained total variation image denoising and deblurring problems. IEEE Transactions on Image Processing 18(11), 2419–2434 (2009)

    Article  MathSciNet  Google Scholar 

  17. Yuan, B., Su, F., Cai, A.: Fingerprint retrieval approach based on novel minutiae triplet features. In: IEEE International Conference on Biometrics: Theory, Applications and Systems, pp. 170–175 (2012)

    Google Scholar 

  18. Iloanusi, O., Gyaourova, A., Ross, A.: Indexing fingerprints using minutiae quadruplets. In: IEEE International Conference on Computer Vision and Pattern Recognition Workshops, pp. 127–133 (2011)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Engineering and Information Technology, The University of New South Wales, Canberra, ACT, 2600, Australia

    Jinwei Xu & Jiankun Hu

Authors
  1. Jinwei Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jiankun Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jiankun Hu .

Editor information

Editors and Affiliations

  1. Apt. 2A, NEW YORK, New York, USA

    Meikang Qiu

  2. University of Texas, San Antonio, Texas, USA

    Shouhuai Xu

  3. Dept. of Computer Science, Columbia University, New York, New York, USA

    Moti Yung

  4. University of Otago, Dunedin, New Zealand

    Haibo Zhang

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Xu, J., Hu, J. (2015). Multi-constrained Orientation Field Modeling and Its Application for Fingerprint Indexing. In: Qiu, M., Xu, S., Yung, M., Zhang, H. (eds) Network and System Security. NSS 2015. Lecture Notes in Computer Science(), vol 9408. Springer, Cham. https://doi.org/10.1007/978-3-319-25645-0_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-25645-0_12

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25644-3

  • Online ISBN: 978-3-319-25645-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation