Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Seam carving for content-aware image resizing
ACM SIGGRAPH 2007 papers
Detection of seam carving and localization of seam insertions in digital images
Proceedings of the 11th ACM workshop on Multimedia and security
A comparative study of image retargeting
ACM SIGGRAPH Asia 2010 papers
Robust and secure image hashing
IEEE Transactions on Information Forensics and Security
A patch analysis method to detect seam carved images
Pattern Recognition Letters
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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.