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Automated Image Forgery Detection through Classification of JPEG Ghosts

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNIP,volume 7476)

Abstract

We present a method for automating the detection of the so-called JPEG ghost s. JPEG ghost s can be used for discriminating single- and double JPEG compression, which is a common cue for image manipulation detection. The JPEG ghost scheme is particularly well-suited for non-technical experts, but the manual search for such ghost s can be both tedious and error-prone. In this paper, we propose a method that automatically and efficiently discriminates single- and double-compressed regions based on the JPEG ghost principle. Experiments show that the detection results are highly competitive with state-of-the-art methods, for both, aligned and shifted JPEG grids in double-JPEG compression.

Keywords

  • Independent Component Analysis
  • JPEG Image
  • Forgery Detection
  • Image Forensic
  • Grid Alignment

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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© 2012 Springer-Verlag Berlin Heidelberg

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Zach, F., Riess, C., Angelopoulou, E. (2012). Automated Image Forgery Detection through Classification of JPEG Ghosts. In: Pinz, A., Pock, T., Bischof, H., Leberl, F. (eds) Pattern Recognition. DAGM/OAGM 2012. Lecture Notes in Computer Science, vol 7476. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32717-9_19

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  • DOI: https://doi.org/10.1007/978-3-642-32717-9_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32716-2

  • Online ISBN: 978-3-642-32717-9

  • eBook Packages: Computer ScienceComputer Science (R0)