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首页> 外文会议>IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology >Copy Move Forgery using Hu's Invariant Moments and Log-Polar Transformations
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Copy Move Forgery using Hu's Invariant Moments and Log-Polar Transformations

机译：复制使用HU的不变矩和逻辑极化转换移动伪造

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摘要

With the increase in interchange of data, there is a growing necessity of security. Considering the volumes of digital data that is transmitted, they are in need to be secure. Among the many forms of tampering possible, one widespread technique is Copy Move Forgery (CMF). This forgery occurs when parts of the image are copied and duplicated elsewhere in the same image. There exist a number of algorithms to detect such a forgery in which the primary step involved is feature extraction. The feature extraction techniques employed must have lesser time and space complexity involved for an efficient and faster processing of media. Also, majority of the existing state of art techniques often tend to falsely match similar genuine objects as copy move forged during the detection process. To tackle these problems, the paper proposes a novel algorithm that recognizes a unique approach of using Hu's Invariant Moments and Log-polar Transformations to reduce feature vector dimension to one feature per block simultaneously detecting CMF among genuine similar objects in an image. The qualitative and quantitative results obtained demonstrate the effectiveness of this algorithm.
机译：随着数据的相互交换的增加，有安全的成长需要。考虑到传输数字数据的量，他们需要是安全的。在篡改可能的多种形式，广泛的一个方法是复制移动伪造（CMF）。当图像的部分被复制，在同一图像中别处复制时发生此伪造。存在一些算法，以检测这样的伪造，其中所涉及的主要步骤是特征提取。所使用的特征提取技术必须具有较小时间和空间涉及一种高效的复杂性和媒体更快的处理。另外，大多数的现有技术的技术的存在状态的往往倾向于错误地匹配相似真正对象作为在检测过程伪造复制移动。为了解决这些问题，提出了一种新颖的算法，该算法可以识别使用胡的不变矩和Log极性转换，以减少的特征向量的维度每块的图像真正相似对象中同时检测CMF一个特征的独特的方法。所获得的定性和定量结果表明，该算法的有效性。

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