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Copy move forgery detection using SIFT and GMM

机译:使用SIFT和GMM的复制移动伪造检测

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Modifying or enhancing an image is ubiquitous but, when enhancement tends to change the interpretation of the image they are termed as an attempt of forgery on digital images. Copy move forgery (CMF) is a simple technique and has a number of well built tools in a number of image enhancement software. CMF detection techniques often tend to establish similarity between copied and pasted region on the same image as both are from same original image. Keypoint and block based techniques are used to determine the CMF. SIFT keypoints are combined with different techniques to accurately localize forgery. High dimensionality of feature vector acts as a bottle neck in SIFT based analysis. We propose a method to detect CMF using SIFT descriptors which are clustered using GMM and segment the obtained suspect region speeding up the analysis.
机译:修改或增强图像是普遍存在的,但是,当增强倾向于改变图像的解释时,它们被称为对数字图像进行伪造的尝试。复制移动伪造(CMF)是一种简单的技术,并且在许多图像增强软件中具有许多功能完善的工具。 CMF检测技术通常倾向于在同一图像上的复制区域和粘贴区域之间建立相似性,因为两者均来自同一原始图像。基于关键点和块的技术用于确定CMF。 SIFT关键点与不同技术结合以准确定位伪造。特征向量的高维性在基于SIFT的分析中成为瓶颈。我们提出一种使用SIFT描述符检测CMF的方法,该描述符使用GMM进行聚类,并对获得的可疑区域进行分段,从而加快分析速度。

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