Seam carving estimation using forensic hash

Seam carving is an adaptive multimedia retargeting technique to resize multimedia data for different display sizes. This technique has found promising applications in media consumption on mobile devices such as tablets and smartphones. However, seam carving can also be used to maliciously alter image content and when combined with other tampering operations, makes tampering detection very difficult by traditional multimedia forensic techniques. In this paper, we study the problem of seam carving estimation and tampering localization using very compact side information called forensic hash. The forensic hash technique bridges two related areas, namely robust image hashing and blind multimedia forensics, to answer a broader scope of forensic questions in a more efficient and accurate manner. We show that our recently proposed forensic hash construction can be extended to accurately estimate seam carving and detect local tampering.