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Illuminant inconsistencies for image splicing detection in forensics

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Illuminant maps analysis for image splicing detection

A illuminant inconsistencies-based method for detecting image splicing. Master thesis project on illuminant maps analysis.

Project structure

  • articles: a set of references
  • docs: the thesis documentations and reviews
  • dataset: the dataset folder containing evaluation images
  • source: the source code

References

  • Carvalho et al., "Illuminant-Based Transformed Spaces for Image Forensics"
  • Carvalho, Christian Riess, Elli Angelopoulou, Helio Pedrini, Anderson Rocha, "Exposing Digital Image Forgeries by Illumination Color Classification", IEEE Transactions on Information Forensics and Security, vol. 8, no. 7, pp. 1182-1194, July 2013.
  • Christian Riess and Elli Angelopoulou, "Scene Illumination as an Indicator of Image Manipulation", Information Hiding Conference, June 2010, pp. 66-80.
  • V. Schetinger et al., "Exploring Statistical Differences Between Illuminant Estimation Methods for Exposing Digital Forgeries".

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Illuminant inconsistencies for image splicing detection in forensics

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  • C 52.6%
  • C++ 28.7%
  • Python 10.2%
  • MATLAB 5.6%
  • CMake 1.6%
  • Makefile 1.3%