Abstract: Source camera identification is the process of discerning which camera has been used to capture a particular image. In this paper, we consider the more fundamental problem of trying to classify images captured by a limited number of camera models. Inspired by the previous work that uses sensor imperfection, we propose to use the intrinsic lens aberration as features in the classification. In particular, we focus on lens radial distortion as the primary distinctive feature. For each image under investigation, parameters from pixel intensities and aberration measurements are obtained. We then employ a classifier to identify the source camera of an image. Simulation is carried out to evaluate the success rate of our method. The results show that this is a viable procedure in source camera identification with a high probability of accuracy. Comparing with the procedures using only image intensities, our approach improves the accuracy from 87% to 91%.

  doi          = {10.1117/12.649775},
  urltype      = {Subscription},
  url          = {http://spiedl.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=PSISDG00606900000160690J000001&idtype=cvips&gifs=yes},
  series       = {Presented at the Society of Photo-Optical Instrumentation Engineers (SPIE) Conference},
  booktitle    = {Digital Photography II.  Edited by Sampat, Nitin; DiCarlo, Jeffrey M.; Martin, Russel A.    Proceedings of the SPIE, Volume 6069, pp. 172-179 (2006).},
  author       = {Kai San Choi and Edmund Y. Lam and Kenneth K. Y Wong},
  adsnote      = {Provided by the SAO/NASA Astrophysics Data System},
  month        = {feb},
  volume       = {6069},
  editor       = {Sampat, N. and DiCarlo, J.~M. and Martin, R.~A.},
  year         = {2006},
  title        = {Source camera identification using footprints from lens aberration},
  pages        = {172-179},
  adsurl       = {http://adsabs.harvard.edu/abs/2006SPIE},