Abstract: In this paper, we focus on improving re-sampling detectors for JPEG images. Current detectors can reliably detect re-sampling in JPEG images only up to a Quality Factor (QF) of 95 or higher. At lower QFs, periodic blocking artifacts interfere with periodic patterns of re-sampling. We add a controlled amount of noise to the image before the re-sampling detection step. Adding noise suppresses the JPEG artifacts while the periodic patterns due to re-sampling are partially retained. JPEG images of QF range 75-90 are considered. Gaussian/Uniform noise in the range of 28-24 dB is added to the image and the images thus formed are passed to the re-sampling detector. The detector outputs are averaged to get a final output from which re-sampling can be detected even at lower QFs. We consider two re-sampling detectors - one proposed by Poposcu and Farid [1], which works well on TIFF/mildly compressed JPEG images and the other by Gallagher [2], which is robust on JPEG images but can detect mainly scaled images. For multiple re-sampling operations (rotation, scaling, etc) we show that the re-sampling order matters. If the final operation is up-scaling, it can still be detected even at very low QFs.

@inproceedings{nataraj-sarkar-manjunath-spie10,
  url          = {http://adsabs.harvard.edu/abs/2010SPIE.7541E..17N},
  booktitle    = {SPIE Conference on Media Forensics and Security},
  author       = {Lakshmanan Nataraj and Anindya Sarkar and Bangalore S. Manjunath},
  location     = {San Jose, CA},
  year         = {2010},
  title        = {Improving re-sampling detection by adding noise},
}