A Digital Forgery Image Detection Algorithm Based on Wavelet Homomorphic Filtering | SpringerLink
Skip to main content

A Digital Forgery Image Detection Algorithm Based on Wavelet Homomorphic Filtering

  • Conference paper
Digital Watermarking (IWDW 2008)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 5450))

Included in the following conference series:

Abstract

A novel forgery image detection algorithm is proposed to recognize some traces of artificial blur operation that is one of common ways to forge a digital image. Firstly, a wavelet homonorphic filtering is applied to enhance the high frequency edges after the blurring process. Secondly, the natural edges are eroded by mathematical morphology method, and then the enhanced artificial blur edges are preserved. Finally, the forgery image regions are localized by the region labeling method. Experimental results demonstrate the proposed method can detect forgery area accurately and reduce the detecting errors when some artificial blur operations are used to create a forgery image.

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

Access this chapter

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
JPY 3498
Price includes VAT (Japan)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
JPY 5719
Price includes VAT (Japan)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
JPY 7149
Price includes VAT (Japan)
  • 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.

Similar content being viewed by others

References

  1. Popescu, A., Farid, H.: Exposing digital forgeries by detecting traces of re-sampling. IEEE Transactions on Signal Processing, 758–767 (2005)

    Google Scholar 

  2. Popescu, A., Farid, H.: Statistical tools for digital forensics. In: Fridrich, J. (ed.) IH 2004. LNCS, vol. 3200, pp. 128–147. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  3. Popescu, A., Farid, H.: Exposing digital forgeries by detecting duplicated image regions. Technical report, Dartmouth College, Computer Science (2004)

    Google Scholar 

  4. Luo, W., Huang, J., Qiu, G.: Robust detection of region-duplication forgery in digital image. J. Chinese Journal of Computers, 1998–2007 (2007)

    Google Scholar 

  5. Zhou, L., Wang, D., Guo, Y., Zhang, J.: Blue detection of digital forgery using mathematical morphology. Technical report, KES AMSTA (2007)

    Google Scholar 

  6. Zhang, C., Zhang, H.: Detecting digital image forgeries through weighted local entroy. In: IEEE International Symposium on Signal Processing and Information Technology, pp. 62–67 (2007)

    Google Scholar 

  7. Hsiao, D., Pei, S.: Detecting digital tampering by blur estimation. In: Systematic Approaches to Digital Forensic Engineering, pp. 264–278 (2005)

    Google Scholar 

  8. Zhou, L.: Study of digital forensics based on image content, Beijing University of Posts and Telecommunications (2007)

    Google Scholar 

  9. Daubechies, I.: Ten lectures on wavelet. Capital city press, Philadephia (1992)

    Book  MATH  Google Scholar 

  10. Mallat, S.: A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans. on Pattern Anal. Machine Intell., 674–693 (1989)

    Google Scholar 

  11. Shen, L., Zhang, X.: Image contrast enhancement by wavelet based homomorphic filtering. Chinese Journal of Electronics, 530–534 (2001)

    Google Scholar 

  12. Voicu, L.I., Myler, H.R., Weeks, A.R.: Practical considerations on color image enhancement using homomorphic filtering. Journal of Electronic Imaging, 108–113 (1997)

    Google Scholar 

  13. Ng, T.T., Chang, S.F.: A model for image splicing. In: IEEE International Conference on Image Processing, pp. 1169–1172 (2004)

    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

Zheng, J., Liu, M. (2009). A Digital Forgery Image Detection Algorithm Based on Wavelet Homomorphic Filtering. In: Kim, HJ., Katzenbeisser, S., Ho, A.T.S. (eds) Digital Watermarking. IWDW 2008. Lecture Notes in Computer Science, vol 5450. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04438-0_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-04438-0_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04437-3

  • Online ISBN: 978-3-642-04438-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics