Abstract: In this paper, we demonstrate that it is possible to use the sensor’s pattern noise for digital camera identification from images. The pattern noise is extracted from the images using a wavelet-based denoising filter. For each camera under investigation, we first determine its reference pattern, which serves as a unique identification fingerprint. This could be done using the process of flat-fielding, if we have the camera in possession, or by averaging the noise obtained from multiple images, which is the option taken in this paper. To identify the camera from a given image, we consider the reference pattern noise as a high-frequency spread spectrum watermark, whose presence in the image is established using a correlation detector. Using this approach, we were able to identify the correct camera out of 9 cameras without a single misclassification for several thousand images. Furthermore, it is possible to perform reliable identification even from images that underwent subsequent JPEG compression and/or resizing. These claims are supported by experiments on 9 different cameras including two cameras of exactly the same model.

  publisher    = {SPIE},
  author       = {Jan Luk\'{a}\v{s} and Jessica Fridrich and Miroslav Goljan},
  url          = {http://www.ws.binghamton.edu/fridrich/Research/EI5685-29_Forensic.pdf},
  journal      = {Proceedings of SPIE},
  volume       = {5685},
  year         = {2005},
  title        = {Determining digital image origin using sensor imperfections},
  pages        = {249},