Skip to main content
SpringerLink
Log in

Frequency-Based Fingerprint Recognition

  • Chapter
Handbook of Remote Biometrics

Part of the book series: Advances in Pattern Recognition ((ACVPR))

  • 2082 Accesses

Abstract

abstract Fingerprint recognition is one of the most popular methods used for identification with greater success degree. Fingerprint has unique characteristics called minutiae, which are points where a curve track ends, intersects, or branches off. In this chapter a fingerprint recognition method is proposed in which a combination of fast Fourier transform (FFT) and Gabor filters is used for image enhancement. A novel recognition stage using local features for recognition is also proposed. Also a verification stage is introduced to be used when the system output has more than one person.

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 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover 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. M. Kuchen, C. Newell, A Model for fingerprint formation, Europhysics Letters, 68(1):141–147, 2004.

    Article  Google Scholar 

  2. T. Matsumoto, H. Matsumoto, K. Yamada, S. Hoshino, Impact of artificial gummy fingers on fingerprint systems, SPIE. 4677, 2002.

    Google Scholar 

  3. A. K. Jain and A. Ross, Multibiometric systems, communications of the ACM, Special Issue on Multimodal Interfaces, 47(1):34–40, January 2004.

    Google Scholar 

  4. R. Brunelli, D. Falavigna, Person identification using multiple cues, IEEE Transactions on Pattern Analysis and Machine Intelligence, 17:955–966, October 1995.

    Article  Google Scholar 

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

    Article  Google Scholar 

  6. S. Qian, D. Chen, Joint time-frequency analysis, Methods and Applications, Prentice Hall, Upper Saddle River, 1996.

    Google Scholar 

  7. B. G. Sherlock, D. M. Monro, K. Millard, Fingerprint enhancement by directional Fourier filtering, Visual Image Signal Processing, 141:87–94, 1994.

    Article  Google Scholar 

  8. D. Eberly, Skeletonization of 2D Binary Images, Geometric Tools, Inc., June 2001.

    Google Scholar 

  9. G. Aguilar, G. Sanchez, K. Toscano, M. Nakano, H. Perez, Multimodal biometric system using fingerprint, International Conference on Intelligence and Advance Systems, November 2007.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. SEPI ESIME Culhuacan, Instituto Politécnico Nacional, Av. Santa Ana 1000, México D.F

    Gualberto Aguilar, Gabriel Sánchez, Karina Toscano & Héctor Pérez

Authors
  1. Gualberto Aguilar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gabriel Sánchez
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Karina Toscano
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Héctor Pérez
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Gualberto Aguilar .

Editor information

Editors and Affiliations

  1. Universitá of Sassari, Dipto. Architettura e Pianificazione, Piazza Duomo, 6, 07041 Alghero SS, Italy

    Massimo Tistarelli (Prof.) (Prof.)

  2. Chinese Academy of Science Institute of Automation, Center Biometrics Research & Security, Room 1227, Zhongguancun 95, 100080 Beijing, China

    Stan Z. Li

  3. University of Maryland, Center for Automation Research, College Park, MD 20742-3275, USA

    Rama Chellappa

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag London Limited

About this chapter

Cite this chapter

Aguilar, G., Sánchez, G., Toscano, K., Pérez, H. (2009). Frequency-Based Fingerprint Recognition. In: Tistarelli, M., Li, S.Z., Chellappa, R. (eds) Handbook of Remote Biometrics. Advances in Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-84882-385-3_16

Download citation

  • DOI: https://doi.org/10.1007/978-1-84882-385-3_16

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84882-384-6

  • Online ISBN: 978-1-84882-385-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation