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Copy move forgery detection using DCT, PatchMatch and cellular automata
Multimedia Tools and Applications ( IF 3.6 ) Pub Date : 2021-07-27 , DOI: 10.1007/s11042-021-11174-7
Gulnawaz Gani 1 , Fasel Qadir 1
Affiliation  

Copy-move image forgery is a type of digital image forgery where content is copied and pasted within the same image, either by hiding foreground objects within an image by copying a background region over them or by emphasizing some foreground objects of the image through duplication. To prevent any consequences arising from the consumption of these forged images, many Copy-Move Forgery Detection (CMFD) techniques have been proposed in the past that analyze a suspected input image for a possible copy-move forgery. However, the existing detectors show limited detection accuracy in presence of post-processing manipulations like noise addition, compression, blur etc., which, in turn, are often used to hide the traces of tampering and produce convincing forgeries. In this paper, we propose a block-based CMFD technique which works well under these post-processing manipulations. We use Discrete Cosine Transform and Cellular Automata to extract features from the image blocks, which are subsequently matched using the patch match algorithm. Also, to extract the cloned regions corresponding to the matched features in a reliable way, we propose a simple and efficient CA-based post-processing procedure. The experimental results on the standard dataset demonstrate the effectiveness of our method for detecting copy-move forgeries under diverse post-processing manipulations of noise, compression, blur, brightness change, contrast change and their combinations.



中文翻译:

使用 DCT、PatchMatch 和元胞自动机进行复制移动伪造检测

复制移动图像伪造是一种数字图像伪造,其中内容被复制并粘贴到同一图像中,方法是通过复制背景区域将前景对象隐藏在图像中,或者通过复制来强调图像的某些前景对象。为了防止因使用这些伪造图像而产生的任何后果,过去已经提出了许多复制移动伪造检测 (CMFD) 技术,这些技术分析可疑的输入图像以寻找可能的复制移动伪造。然而,现有的检测器在存在诸如噪声添加、压缩、模糊等后处理操作的情况下显示出有限的检测精度,而这些操作又通常用于隐藏篡改痕迹并产生令人信服的伪造。在本文中,我们提出了一种基于块的 CMFD 技术,该技术在这些后处理操作下运行良好。我们使用离散余弦变换和元胞自动机从图像块中提取特征,然后使用补丁匹配算法进行匹配。此外,为了以可靠的方式提取与匹配特征对应的克隆区域,我们提出了一种简单有效的基于 CA 的后处理程序。在标准数据集上的实验结果证明了我们的方法在噪声、压缩、模糊、亮度变化、对比度变化及其组合的各种后处理操作下检测复制移动伪造的有效性。随后使用补丁匹配算法进行匹配。此外,为了以可靠的方式提取与匹配特征对应的克隆区域,我们提出了一种简单有效的基于 CA 的后处理程序。在标准数据集上的实验结果证明了我们的方法在噪声、压缩、模糊、亮度变化、对比度变化及其组合的各种后处理操作下检测复制移动伪造的有效性。随后使用补丁匹配算法进行匹配。此外,为了以可靠的方式提取与匹配特征对应的克隆区域,我们提出了一种简单有效的基于 CA 的后处理程序。在标准数据集上的实验结果证明了我们的方法在噪声、压缩、模糊、亮度变化、对比度变化及其组合的各种后处理操作下检测复制移动伪造的有效性。

更新日期:2021-07-28
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