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.

随着简单图像编辑软件的广泛应用，伪造图像已成为严重的社会问题，具有极大的破坏作用。复制移动伪造技术通常用于通过复制图像的某些区域并将其粘贴到同一图像中的某处来对图像进行调整。在本文中，提出了一种新的算法来检测复制移动伪造。首先，使用关键点提取算法计算输入图像的关键点。其次，关键点匹配算法用于匹配与候选关键点对相似的关键点。第三，提出了一种新颖的两阶段过滤算法，包括基于网格的过滤器和基于聚类的过滤器，以过滤掉大多数错误匹配的关键点对。随后，通过Delaunay三角剖分算法实现图像消光，以便标记的区域指示伪造区域。使用三个复制移动伪造数据集将所提出算法的性能与某些最新算法进行比较。实验结果表明，该算法的整体性能优于其他检测复制移动伪造图像的解决方案。