Abstract: The quick advance in image/video editing techniques has enabled people to synthesize realistic images/videos conveniently. Some legal issues may arise when a tampered image cannot be distinguished from a real one by visual examination. In this paper, we focus on JPEG images and propose detecting tampered images by examining the double quantization effect hidden among the discrete cosine transform (DCT) coefficients. To our knowledge, our approach is the only one to date that can automatically locate the tampered region, while it has several additional advantages: fine-grained detection at the scale of 8×8 DCT blocks, insensitivity to different kinds of forgery methods (such as alpha matting and inpainting, in addition to simple image cut/paste), the ability to work without fully decompressing the JPEG images, and the fast speed. Experimental results on JPEG images are promising.

  author       = {Zhouchen Lin and Junfeng He and Xiaoou Tang and Chi-Keung Tang},
  url          = {http://linkinghub.elsevier.com/retrieve/pii/S0031320309001198},
  title        = {Fast, automatic and fine-grained tampered {JPEG} image detection via {DCT} coefficient analysis},
  year         = {2009},
  keywords     = {Image Forensics; Tamper Detection; JPEG},
  journal      = {Pattern Recognition},