Abstract: In this paper, we revisit the problem of digital camera sensor identification using photo-response non-uniformity noise (PRNU). Considering the identification task as a joint estimation and detection problem, we use a simplified model for the sensor output and then derive a Maximum Likelihood estimator of the PRNU. The model is also used to design optimal test statistics for detection of PRNU in a specific image. To estimate unknown shaping factors and determine the distribution of the test statistics for the image-camera match, we construct a predictor of the test statistics on small image blocks. This enables us to obtain conservative estimates of false rejection rates for each image under Neyman-Pearson testing. We also point out a few pitfalls in camera identification using PRNU and ways to overcome them by preprocessing the estimated PRNU before identification.

  doi          = {10.1117/12.703370},
  author       = {Mo Chen and Jessica Fridrich and Miroslav Goljan},
  url          = {http://www.ws.binghamton.edu/fridrich/Research/EI6505-25.pdf},
  series       = {Presented at the Society of Photo-Optical Instrumentation Engineers (SPIE) Conference},
  booktitle    = {Security, Steganography, and Watermarking of Multimedia Contents IX.  Edited by Delp, Edward J., III; Wong, Ping Wah.  Proceedings of the SPIE, Volume 6505, pp. 65050P (2007).},
  adsnote      = {Provided by the SAO/NASA Astrophysics Data System},
  month        = {feb},
  volume       = {6505},
  year         = {2007},
  title        = {Digital imaging sensor identification (further study)},
  adsurl       = {http://adsabs.harvard.edu/abs/2007SPIE.6505E..24C},