An efficient and robust method for detecting copy-move forgery

TLDR

Copy‑move forgery is a form of image tampering where a region is duplicated within the same image. The paper proposes a new detection approach that is robust to lossy compression, scaling, and rotation. The method employs counting bloom filters instead of lexicographic sorting to reduce computational complexity while locating duplicated regions. Experiments demonstrate accurate detection of duplicated regions under severe manipulations, with counting bloom filters providing a speed advantage at the cost of a slight loss in robustness.

Abstract

Copy-move forgery is a specific type of image tampering, where a part of the image is copied and pasted on another part of the same image. In this paper, we propose a new approach for detecting copy-move forgery in digital images, which is considerably more robust to lossy compression, scaling and rotation type of manipulations. Also, to improve the computational complexity in detecting the duplicated image regions, we propose to use the notion of counting bloom filters as an alternative to lexicographic sorting, which is a common component of most of the proposed copy-move forgery detection schemes. Our experimental results show that the proposed features can detect duplicated region in the images very accurately, even when the copied region was undergone severe image manipulations. In addition, it is observed that use of counting bloom filters offers a considerable improvement in time efficiency at the expense of a slight reduction in the robustness.