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Fuzzy Metaheuristic Algorithm for Copy-Move Forgery Detection in Image

机译:图像复制运动伪造的模糊元启发式算法

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One of the most common methods for counterfeiting digital images is copy-move forgery detection (CMFD). It implies that part of the image is copied and pasted to another part of the same image. The purpose of such changes is to hide certain image content, or to duplicate image content. The aim of this paper is to propose a new clustering algorithm for edited images. The image is divided into non-overlapping blocks. New fuzzy metric is used to calculate the distance between the blocks. In this research the metaheuristic method of the variable neighbourhood search (VNS) is used for the classification of the block. The aim of the classification is that the division should be on the changed and unchanged blocks. The results of this research are compared with the latest results from the literature dealing with this problem and it is shown that the proposed algorithm gives better results. Publicly available image databases were used. The proposed algorithm was implemented in the Python programming language.
机译:伪造数字图像的最常见方法之一是复制移动伪造检测(CMFD)。这意味着将图像的一部分复制并粘贴到同一图像的另一部分。此类更改的目的是隐藏某些图像内容或复制图像内容。本文的目的是为编辑图像提出一种新的聚类算法。图像分为非重叠块。新的模糊度量用于计算块之间的距离。在这项研究中,将可变邻域搜索(VNS)的元启发式方法用于块的分类。分类的目的是,划分应该针对已更改和未更改的块。将该研究结果与文献中有关该问题的最新结果进行了比较,结果表明所提出的算法给出了更好的结果。使用公开可用的图像数据库。所提出的算法是用Python编程语言实现的。

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