Abstract: Digital images can be captured or generated by a variety of sources including digital cameras, scanners and computer graphics softwares. In many cases it is important to be able to determine the source of a digital image such as for criminal and forensic investigation. This paper presents methods for distinguishing between an image captured using a digital camera, a computer generated image and an image captured using a scanner. The method proposed here is based on the differences in the image generation processes used in these devices and is independent of the image content. The method is based on using features of the residual pattern noise that exist in images obtained from digital cameras and scanners. The residual noise present in computer generated images does not have structures similar to the pattern noise of cameras and scanners. The experiments show that a feature based approach using an SVM classifier gives high accuracy.

  url          = {http://cobweb.ecn.purdue.edu/~prints/public/papers/icassp08-nitin.pdf},
  booktitle    = {Proceedings of the 2008 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2008)},
  author       = {Nitin Khanna and George T. -C Chiu and Jan P. Allebach and Edward J. Delp},
  year         = {2008},
  title        = {Forensic techniques for classifying scanner, computer generated and digital camera images},
  pages        = {1653--1656},