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Local JPEG Grid Detector via Blocking Artifacts, a Forgery Detection Tool
Tina Nikoukhah, Miguel Colom, Jean-Michel Morel, Rafael Grompone von Gioi

Local JPEG Grid Detector via Blocking Artifacts, a Forgery Detection Tool

Science & Mathematics Published 2020 Verification Pending

Overview & Synopsis

Image JPEG compression leaves blocking artifact traces. This paper describes an algorithm that exploits those traces to locally recover the grid embedded in the image by the JPEG compression. The algorithm returns a list of grids associated with different parts of the image. The method uses Chen and Hsu's cross-difference to reveal the artifacts. Then, an a contrario validation step according to Desolneux, Moisan and Morel's theory delivers for each detected grid a Number of False Alarms (NFA) which tells how unlikely it is that the detection is due to chance. The only parameter is the step size of the windows used, which represents the exhaustiveness of the method. The application to image forgery detection is twofold: first, the presence of discrepant JPEG grids with low NFA is a strong forgery cue; second, knowledge of the grid is anyway required for further JPEG forensic analysis. Source Code The reviewed source code and documentation for this algorithm are available from the web page of this article 1. Compilation and usage instruction are included in the README.txt file of the archive.

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Document Information

Document Title Local JPEG Grid Detector via Blocking Artifacts, a Forgery Detection Tool
Author / Organization Tina Nikoukhah, Miguel Colom, Jean-Michel Morel, Rafael Grompone von Gioi
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2020
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-18287
Original Source Link Visit Source Page on hal.science »