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Robust and effective multiple copy-move forgeries detection and localization

机译：鲁棒和有效的多重复印备手备忘录检测和本地化

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摘要

Copy-move (or copy-paste or cloning) is one of the most common image forgeries, wherein one or more region are copied and pasted within the same image. The motivations of such forgery include hiding an element in the image or emphasizing a particular object. Copy-move image forgery is more challenging to detect than other types, such as splicing and retouching. In recent years, keypoint based copy-move forgery detection, which extracts image keypoints and uses local visual features to identify duplicated regions, exhibits remarkable performance with respect to memory requirement and robustness against various attacks. However, these approaches usually have poor detection ability when copy-move forgeries only involve small or smooth regions. Moreover, they cannot always effectively deal with multiple copy-move forgeries. To tackle these challenges, we propose a robust and effective multiple copy-move forgeries detection and localization method through adaptive keypoint extraction, robust local feature representation, and offsets clustering based post-processing. Firstly, we develop a new image keypoint detector, named generic features from accelerated segment test, and extract adaptively the uniform distribution keypoints from the forged image by employing the adaptive-thresholding and non-maximum suppression. Then, we introduce fast quaternion polar complex exponential transform to describe the image keypoints compactly and distinctively, and utilize the KD tree based K-nearest neighbor matching to find possible correspondences. Finally, the falsely matched pairs are removed by employing the offsets information based candidate clustering, and the duplicated regions are localized using RANSAC and ZNCC algorithm. We conduct extensive experiments to evaluate the performance of the proposed approach, in which encouraging results validate the effectiveness of the proposed technique, especially for plain/multiple copy-move forgeries, in comparison with the state-of-the-art approaches recently proposed in the literature.
机译：复制 - 移动（或复制粘贴或克隆）是最常见的图像伪造者之一，其中复制一个或多个区域并粘贴在同一图像内。这种伪造的动机包括掩藏图像中的元素或强调特定对象。复制移动图像伪造比其他类型更具挑战性，例如拼接和修饰。近年来，基于关键点的复制移动伪造检测，其中提取图像键点并使用本地视觉特征来识别重复的区域，相对于内存要求和对各种攻击的鲁棒性表现出显着的性能。然而，当复制备手涉及小或平滑地区时，这些方法通常具有差的检测能力。此外，他们不能总是有效地处理多个复印备伪造。为了解决这些挑战，我们通过自适应键盘提取，强大的本地特征表示和基于后处理的偏移聚类，提出了一种强大而有效的多副本移动备手检测和本地化方法。首先，我们开发一个新的图像keypoint检测器，来自加速段测试的名称通用特征，并通过采用自适应阈值和非最大抑制，自适应地从伪造图像中提取均匀分布关键点。然后，我们引入快速四元数偏光复杂指数变换，以简洁地和明确地描述图像关键点，并利用基于KD树的K-Collect邻居匹配以找到可能的对应关系。最后，通过采用基于偏移信息的候选聚类来除去虚假匹配的对，并且使用Ransac和Zncc算法本地化重复的区域。我们进行广泛的实验来评估所提出的方法的表现，其中令人鼓舞的结果验证了拟议的技术的有效性，特别是对于最近提出的最先进的方法相比文献。

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  • 来源
    《Pattern Analysis and Applications》 |2021年第3期|1025-1046|共22页
  • 作者

    Wang Xiang-yang; Wang Chao; Wang Li; Yang Hong-ying; Niu Pan-pan;

  • 作者单位

    Liaoning Normal Univ Sch Comp & Informat Technol Dalian 116029 Peoples R China;

    Liaoning Normal Univ Sch Comp & Informat Technol Dalian 116029 Peoples R China;

    Liaoning Normal Univ Sch Comp & Informat Technol Dalian 116029 Peoples R China;

    Liaoning Normal Univ Sch Comp & Informat Technol Dalian 116029 Peoples R China;

    Liaoning Normal Univ Sch Comp & Informat Technol Dalian 116029 Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Copy-move forgery detection; GFAST; FQPCET; Offsets clustering;

    机译：复制 - 移动伪造检测;GFAST;FQPCET;偏移群集;

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