This paper presents a segmentation-based scheme for detecting copy-move forgery in images by first segmenting the image into independent patches and then extracting keypoints for comparison. The detection process involves identifying suspicious patch pairs and estimating an affine transform matrix, followed by a refinement stage using an expectation-maximization algorithm. Experimental results demonstrate the effectiveness of the proposed method compared to existing techniques.

1. SEGMENTATION-BASED IMAGE COPY-MOVE FORGERY DETECTION SCHEME
ABSTRACT
In this paper, we propose a scheme to detectthe copy-move forgery in an image, mainly
by extracting thekeypoints for comparison. The main difference to the traditionalmethods is that
the proposed scheme first segments the testimage into semantically independent patches prior to
keypointextraction. As a result, the copy-move regions can be detected bymatching between
these patches. The matching process consistsof two stages. In the first stage, we find the
suspicious pairsof patches that may contain copy-move forgery regions, and weroughly estimate
an affine transform matrix. In the second stage,an Expectation-Maximization-based algorithm is
designed torefine the estimated matrix and to confirm the existence of copymoveforgery.
Experimental results prove the good performanceof the proposed scheme via comparing it with
the state-of-the-artschemes on the public databases.