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Seam carving is a popular technique for content aware image retargeting. Itcan be used to deliberately manipulate images, for example, change the GPSlocations of a building or insert/remove roads in a satellite image. This paperproposes a novel approach for detecting and localizing seams in such images.While there are methods to detect seam carving based manipulations, this is thefirst time that robust localization and detection of seam carving forgery ismade possible. We also propose a seam localization score (SLS) metric toevaluate the effectiveness of localization. The proposed method is evaluatedextensively on a large collection of images from different sources,demonstrating a high level of detection and localization performance acrossthese datasets. The datasets curated during this work will be released to thepublic.

SeeTheSeams: Localized Detection of Seam Carving based Image Forgery in Satellite Imagery