Abstract: With advances in image display technology, recapturing good-quality images from the high-fidelity artificial scenery on a LCD screen becomes possible. Such image recapturing posts a security threat, which allows the forgery images to bypass the current forensic systems. In this paper, we first recapture some good-quality photos on different LCD screens by properly setting up the recapturing environment and tuning the controllable settings. In a perceptional study, we find that such finely recaptured images can hardly be identified by human eyes. To prevent the image recapturing attack, we propose a set of statistical features, which capture the common anomalies introduced in the camera recapturing process on LCD screens. With a probabilistic support vector machine classifier, comparison results show that our proposed features work very well, which outperform the conventional image forensic features in identification of the finely recaptured images.

  url          = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5495419},
  booktitle    = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
  author       = {Hong Cao and Alex C. Kot},
  location     = {Dallas, TX},
  year         = {2010},
  title        = {Identification of recaptured photographs on {LCD} screens},
  pages        = {1790-1793},