We propose a new algorithm for the reliable detection and localization of video copy-move forgeries. Discovering well crafted video copy-moves may be very difficult, especially when some uniform background is copied to occlude foreground objects. To reliably detect both additive and occlusive copy-moves we use a dense-field approach, with invariant features that guarantee robustness to several post-processing operations. To limit complexity, a suitable video-oriented version of PatchMatch is used, with a multiresolution search strategy, and a focus on volumes of interest. Performance assessment relies on a new dataset, designed ad hoc, with realistic copy-moves and a wide variety of challenging situations. Experimental results show the proposed method to detect and localize video copy-moves with good accuracy even in adverse conditions.
@article{arxiv.1703.04636,
title = {A PatchMatch-based Dense-field Algorithm for Video Copy-Move Detection and Localization},
author = {Luca D'Amiano and Davide Cozzolino and Giovanni Poggi and Luisa Verdoliva},
journal= {arXiv preprint arXiv:1703.04636},
year = {2017}
}