Abstract: The steady improvement in image/video editing techniques has enabled people to synthesize realistic images/videos conveniently. Some legal issues may occur when a doctored image cannot be distinguished from a real one by visual examination. Realizing that it might be impossible to develop a method that is universal for all kinds of images and JPEG is the most frequently used image format, we propose an approach that can detect doctored JPEG images and further locate the doctored parts, by examining the double quantization effect hidden among the DCT coefficients. Up to date, this approach is the only one that can locate the doctored part automatically. And it has several other advantages: the ability to detect images doctored by different kinds of synthesizing methods (such as alpha matting and inpainting, besides simple image cut/paste), the ability to work without fully decompressing the JPEG images, and the fast speed. Experiments show that our method is effective for JPEG images, especially when the compression quality is high.

  publisher    = {Springer Verlag},
  author       = {Junfeng He and Zhouchen Lin and Lifeng Wang and Xiaoou Tang},
  url          = {http://research.microsoft.com/asia/dload_files/group/vc/2007upload/DoctorImage_ECCV06.pdf},
  series       = {Lecture Notes in Computer Science},
  booktitle    = {Computer Vision -- ECCV 2006. 9th European Conference on Computer Vision, Graz, Austria, May 2006, Proceedings, Part III},
  volume       = {LNCS 3953},
  year         = {2006},
  editor       = {Ale\vs Leonardis and Horst Bischof and Axel Pinz},
  address      = {Berlin, Heidelberg},
  title        = {Detecting doctored {JPEG}-images via {DCT} coefficient analysis},
  pages        = {423-435},