Skip to main content

Fake Finger Detection Using the Fractional Fourier Transform

  • Conference paper
Biometric ID Management and Multimodal Communication (BioID 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5707))

Included in the following conference series:

Abstract

This paper introduces a new method for detecting fake finger using the fractional Fourier transform (FrFT). The advantage of this method is to require one fingerprint image. The fingerprint is a texture with the interleaving of ridge and valley. When the fingerprint is transformed into the spectral domain, we found energy of fingerprint. Generally, the energy of live fingerprints is larger than the energy of fake fingerprints. Therefore, the energy in the spectral image of a fingerprint can be a feature for detecting of fake fingers. We transformed the fingerprint image into the spatial frequency domain using 2D Fast Fourier transform and detected a specific line in the spectrum image. This lineis transformed into the fractional Fourier domain using the fractional Fourier transform. And, the standard deviation of it is used to discriminate between fake and live fingerprints. For experiment, we made fake fingers of silicone, gelatin, paper and film. And, the fake finger database is created, by which the performance of a fingerprint verification system can be evaluated with higher precision. The experimental results demonstrate that the proposed method can detect fake fingers.

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 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. Maltoni, D., Maio, D., Jain, A.K., Prabhakar, S.: Handbook of fingerprint Recognition. Springer, New York (2003)

    MATH  Google Scholar 

  2. Matsumoto, T., Matsumoto, H., Yamada, K., Hoshino, S.: Impact of artificial “Gummy” fingers on fingerprint systems. In: Proc. SPIE, vol. 4677 (2002)

    Google Scholar 

  3. Jin, C., Kim, H., Elliott, S.: Liveness Detection of Fingerprint Based on Band-Selective Fourier Spectrum. In: Nam, K.-H., Rhee, G. (eds.) ICISC 2007. LNCS, vol. 4817, pp. 168–179. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  4. Baldisserra, D., Franco, A., Maio, D., Maltoni, D.: Fake Fingerprint Detection by Odor Analysis. In: ICBA 2006. Proceedings International Conference on Biometric Authentication, Hong Kong (2006)

    Google Scholar 

  5. Drahansky, M., Notzel, R., Funk, W.: Liveness Detection based on Fine Movements of the Fingertip Surface. In: 2006 IEEE Information Assurance Workshop, June 21-23, 2006, pp. 42–47 (2006)

    Google Scholar 

  6. van der Putte, T., Keuning, J.: Biometrical fingerprint recognition: don’t get your fingers burned. In: Proceedings of IFIP TC8/WG8.8 Fourth Working Conference on Smart Card Research and Advanced Applications, pp. 289–303. Kluwer Academic Publishers, Dordrecht (2000)

    Google Scholar 

  7. Reddy, P.V., Kumar, A., Rahman, S.M.K., Mundra, T.S.: A New Method for Fingerprint Antispoofing using Pulse Oxiometry. In: IEEE on Biometrics: Theory, Applications, and Systems, Washington DC (2007)

    Google Scholar 

  8. Jia, J., Cai, L., Zhang, K., Chen, D.: A New Approach to Fake Finger Detection Based on Skin Elasticity Analysis. In: Lee, S.-W., Li, S.Z. (eds.) ICB 2007. LNCS, vol. 4642, pp. 309–318. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  9. Antonelli, A., Cappelli, R., Maio, D., Maltoni, D.: Fake Finger Detection by Skin Distortion Analysis. IEEE Transactions on Information Forensics and Security 1(3), 360–373 (2006)

    Article  Google Scholar 

  10. Parthasaradhi, S.T.V., Derakhshani, R., Hornak, L.A., Schuckers, S.A.C.: Time-Series Detection of Perspiration as a Liveness Test in fingerprint Devices. IEEE Trans. on Systems, Man, and Cybernetics - Part C 35(3) (2005)

    Google Scholar 

  11. Ozaktas, H.M., Zalevsky, Z., Alper Kutay, M.: The fractional Fourier Transform: With Applications in Optics and Signal Processing. Wiley, New York (2001)

    Google Scholar 

  12. Wilson, C.L., Watson, C.I., Paek, E.G.: Effect of resolution and image quality on combined optical and neural network fingerprint matching. In: PR, vol. 33(2) (2000)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Lee, Hs., Maeng, Hj., Bae, Ys. (2009). Fake Finger Detection Using the Fractional Fourier Transform. In: Fierrez, J., Ortega-Garcia, J., Esposito, A., Drygajlo, A., Faundez-Zanuy, M. (eds) Biometric ID Management and Multimodal Communication. BioID 2009. Lecture Notes in Computer Science, vol 5707. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04391-8_41

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-04391-8_41

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04390-1

  • Online ISBN: 978-3-642-04391-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics