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If we consider photo forensics within a Bayesian framework, then the probability
that an image has been manipulated given the results of a forensic test can be
expressed as a product of a likelihood term (the probability of a forensic test detecting
manipulation given that an image was manipulated) and a prior term (the probability
that an image was manipulated). Despite the success of many forensic techniques,
the incorporation of a statistical prior has not been previously considered. We describe
a framework for incorporating statistical priors into any forensic analysis and specifically
address the problem of quantifying the probability that a portion of an image is the result
of content-aware fill, cloning, or some other form of information removal. We posit that
the incorporation of such a prior will improve the overall accuracy of a broad range of
Bibliographic citation for this report: [plain text] [BIB] [BibTeX] [Refer]
Or copy and paste:
Wei Fan and Hany Farid, "A Statistical Prior for Photo Forensics: Object Removal." Dartmouth Computer Science Technical Report TR2017-837, October 2017.
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