Algorithm

Statistics

Computer science

Filter (signal processing)

Pattern recognition (psychology)

Mathematics

Image (mathematics)

Artificial intelligence

Matching (statistics)

Delaunay triangulation

Computer vision

Digital Signal Processing

With the wide application of simple image editing software, forgery images have become severe social problems with extremely damaging effects. The copy-move forgery technique is commonly used to temper an image by copying some regions of an image and pasting them somewhere in the same image. In this paper, a novel algorithm is proposed for the detection of copy-move forgery. First, the keypoints of the input image are computed using a keypoint extraction algorithm. Second, a keypoint-matching algorithm is used to match similar keypoints as the candidate keypoint pairs. Third, a proposed novel Two-Stage Filtering algorithm, including the Grid-Based Filter and the Clustering-Based Filter, is applied to filter out most of the false matching keypoint pairs. Subsequently, image matting is achieved by the Delaunay triangulation algorithm so that the marked areas indicate the forgery regions. Three copy-move forgery datasets are used to compare the performances of the proposed algorithm with some state-of-the-art algorithms. The experimental results demonstrate that the proposed algorithm's overall performance is superior to other solutions for detecting copy-move forgery images.

A novel copy-move forgery detection algorithm via two-stage filtering