Abstract: In non-intrusive forensic analysis, we wish to find information and properties about a piece of data without any reference to the original data prior to processing. An important first step to forensic analysis is the detection and estimation of block processing. Most existing work in block measurement uses strong assumptions on the data related to the block size or the method of compression. In this paper, we propose a new method to estimate the block size in digital images in a blind manner for use in a forensic context. We make no assumptions on the block size or the nature of any previous processing. Our scheme can accurately estimate block sizes in images up to a PSNR of 42 dB where block artifacts are perceptually invisible. We also offer a measure of detection accuracy which correctly classifies an image as block-processed with a probability of 95.0% while keeping the probability of false alarm at 7.4%.

  author       = {Steven Tjoa and W. Sabrina Lin and H. Vicky Zhao and K. J. Ray Liu},
  url          = {http://www.ece.ualberta.ca/~vzhao/paper/ICASSP07_block.pdf},
  journal      = {Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on},
  volume       = {1},
  year         = {2007},
  title        = {Block size forensic analysis in digital images},