Image Source Coding Forensics Via Intrinsic Fingerprints

  • W. Sabrina Lin, Steven Tjoa, H. Vicky Zhao, and K. J. Ray Liu
  • IEEE Int. Conf. Multimedia and Expo, July 2007
  • Download: Paper, BibTeX 
    @INPROCEEDINGS{lin2007icme,
  title = "Image Source Coding Forensics via Intrinsic Fingerprints",
  author = "W. Sabrina Lin and Steven Tjoa and H. Vicky Zhao and K. J. Ray Liu",
  booktitle = "Proc. IEEE Int. Conf. Multimedia and Expo",
  address = "Beijing, China",
  year = "2007",
  month = jul,
  pages = "1127--1130",
};

The most popular image compression schemes in use today are lossy, i.e., compression imposes some irreversible distortion in the image in order to achieve a smaller file size. Because each compression method imposes different kinds of distortion, the distortion can act as a fingerprint of the compression method. Existing image compression methods can be grouped into a few categories — e.g., transform coding, vector quantization, subband coding, linear predictive coding, embedded coding — where all methods in the same category leave behind the same type of fingerprint in an image during compression.

In this paper, we analyze the intrinsic fingerprints of different types of image compression methods and propose a forensic system that identifies the type of the compression and provides a confidence measure in the system’s decision. Results show that the system can achieve a probability of detection of 0.82 for an image PSNR of 40 dB and even higher accuracy for lower PSNRs.