forgery & forensics hany farid acm proceedings of the 8th workshop on multimedia and security,...
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Forgery & Forensics
Hany FaridACM Proceedings of the 8th Workshop
onMultimedia and Security, Sep. 2006
Image Tampering
Digital Tampering: Compositing. Morphing. Re-touching. Enhancing. Computer graphics. Painted.
Forensics
Forensic science, the application of a broad spectrum of sciences to answer questions of interest to the legal system.
Digital forensics, the application of the scientific method to digital media in order to establish factual information for judicial review.
Discussion
The problem of detecting digital forgeries is a complex one with no universally applicable solution.
Reliable forgery detection should be approached from multiple directions.
Exposing Digital Forgeries in Scientific Images
In at least one journal, it is estimated that as many as 20% of accepted manuscripts contain figures with inappropriate manipulations, and 1% with fraudulent manipulations.
Image Manipulation
Action of each manipulation scheme:
Deletion, (a). A band was erased.
Healing, (b). Several bands were
removing using Photoshop’s “healing brush.”
Duplication, (c). A band was copied and
pasted into a new location.
Image Manipulation
Effect of each manipulation scheme: Deletion.
Remove small amounts of noise that are present through the dark background of the image.
Healing. Disturb the underlying spatial frequency (texture).
Duplication. Leave behind an obvious statistical pattern – two
regions in the image are identical. Formulate the problem of detecting each of
these statistical patterns as an image segmentation problem.
Image Segmentation: Texture
For healing.
Ig (. ): the
magnitude of the image gradient at a given pixel.
Image Segmentation: Texture
s d (. ): 1D deravative
filter. [0.0187 0.1253 0.1930
0.0 −0.1930 −0.1253 −0.0187]
p (. ): low-pass filter. [0.0047 0.0693 0.2454
0.3611 0.2454 0.0693 0.0047]
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Automatic Detection