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

TL;DR

This paper introduces a novel method for detecting and localizing seam carving manipulations in satellite images, providing a new tool for verifying image authenticity and integrity.

Contribution

It presents the first robust approach for localizing seam carving forgeries in satellite imagery, along with a new seam localization score metric.

Findings

High detection accuracy across diverse datasets

Effective localization of seam carving regions

Public release of curated datasets

Abstract

Seam carving is a popular technique for content aware image retargeting. It can be used to deliberately manipulate images, for example, change the GPS locations of a building or insert/remove roads in a satellite image. This paper proposes a novel approach for detecting and localizing seams in such images. While there are methods to detect seam carving based manipulations, this is the first time that robust localization and detection of seam carving forgery is made possible. We also propose a seam localization score (SLS) metric to evaluate the effectiveness of localization. The proposed method is evaluated extensively on a large collection of images from different sources, demonstrating a high level of detection and localization performance across these datasets. The datasets curated during this work will be released to the public.