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Copy-rotate-move forgery detection based on spatial domain

机译:基于空间域的复制-旋转-移动伪造检测

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Digital image tampering becomes a common information falsification trend. Copy-Move forgery is one of the tampering types that are used. Image forgery is the science of detecting image tempering whether with a previous knowledge about the source image (active) or without (passive). In this paper, we propose a method which is efficient and fast for detecting Copy-Move regions even when the copied region was undergone rotation modify in spatial domain. The proposed method accelerates blocking matching strategy by parallel comparing between blocks. Firstly, the image is divided into fixed-size overlapping blocks then features are extracted for each block. k-means clustering technique is used to cluster the blocks into different cluster. The feature vectors of each cluster blocks are lexicographically sorted by radix sort, and then a similarity measure is calculated between each nearby blocks to determine their similarity. The experimental results show that the proposed method can detect the duplicated regions efficiently even when an image was modified by jpeg compression, rotation and smoothing conditions. The proposed system reduced processing time up to 75% of other previous works.
机译:数字图像篡改已成为一种常见的伪造信息趋势。复制移动伪造是使用的篡改类型之一。图像伪造是一门检测图像回火的科学,无论是否具有关于源图像的先前知识(主动)或没有(被动)。在本文中,我们提出了一种即使在复制区域在空间域中进行旋转修改时,也能快速,有效地检测复制移动区域的方法。所提出的方法通过块之间的并行比较来加速块匹配策略。首先,将图像划分为固定大小的重叠块,然后为每个块提取特征。 k-均值聚类技术用于将块聚类为不同的聚类。通过基数排序对每个聚类块的特征向量进行字典排序,然后在每个相邻块之间计算相似性度量,以确定它们的相似性。实验结果表明,即使通过jpeg压缩,旋转和平滑条件修改了图像,该方法也可以有效地检测出重复区域。拟议的系统将处理时间最多减少了其他先前工作的75%。

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