Blind Detection of Region Duplication Forgery Using Fractal Coding and Feature Matching

Jenadeleh, Mohsen; Moghaddam, Mohsen Ebrahimi

doi:10.1111/1556-4029.13108

Cited by 6 publications

(2 citation statements)

References 39 publications

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“…These techniques do not require any additional image information besides the image itself to detect whether it has been modified or not [ 9 ]. Many blind forensics methods have been proposed for the detection of various modifications of natural images including noise addition [ 10 ], median filtering [ 11 ], copy-move modification [ 12 , 13 ], JPEG compression [ 14 ]. Notice that blind forensics techniques can also be used for image steganalysis purpose, that is, to detect whether an image has been modified so as to dissimulate a secret message in between spies [ 15 – 18 ].…”

Section: Introductionmentioning

confidence: 99%

Medical Image Blind Integrity Verification with Krawtchouk Moments

Zhang

Liu

Chen

et al. 2018

International Journal of Biomedical Imaging

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A new blind integrity verification method for medical image is proposed in this paper. It is based on a new kind of image features, known as Krawtchouk moments, which we use to distinguish the original images from the modified ones. Basically, with our scheme, image integrity verification is accomplished by classifying images into the original and modified categories. Experiments conducted on medical images issued from different modalities verified the validity of the proposed method and demonstrated that it can be used to detect and discriminate image modifications of different types with high accuracy. We also compared the performance of our scheme with a state-of-the-art solution suggested for medical images—solution that is based on histogram statistical properties of reorganized block-based Tchebichef moments. Conducted tests proved the better behavior of our image feature set.

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Section: Introductionmentioning

confidence: 99%

Medical Image Blind Integrity Verification with Krawtchouk Moments

Zhang

Liu

Chen

et al. 2018

International Journal of Biomedical Imaging

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“…A number of copy‐move forgery detection (CMFD) methods have been proposed to detect this kind of forgery . In the literature, these existing methods can be classified as either block‐based or keypoint‐based methods .…”

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confidence: 99%

Two‐stage Keypoint Detection Scheme for Region Duplication Forgery Detection in Digital Images

Emam

Han

Zhang

2017

Journal of Forensic Sciences

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ABSTRACT:In digital image forensics, copy-move or region duplication forgery detection became a vital research topic recently. Most of the existing keypoint-based forgery detection methods fail to detect the forgery in the smooth regions, rather than its sensitivity to geometric changes. To solve these problems and detect points which cover all the regions, we proposed two steps for keypoint detection. First, we employed the scale-invariant feature operator to detect the spatially distributed keypoints from the textured regions. Second, the keypoints from the missing regions are detected using Harris corner detector with nonmaximal suppression to evenly distribute the detected keypoints. To improve the matching performance, local feature points are described using Multi-support Region Order-based Gradient Histogram descriptor. Based on precision-recall rates and commonly tested dataset, comprehensive performance evaluation is performed. The results demonstrated that the proposed scheme has better detection and robustness against some geometric transformation attacks compared with state-of-the-art methods.

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