PCET based copy-move forgery detection in images under geometric transforms

Emam, Mahmoud; Han, Qi; Niu, Xiamu

doi:10.1007/s11042-015-2872-2

Cited by 80 publications

(46 citation statements)

References 16 publications

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“…The detection performance of the proposed CMFD is compared with that of the state-ofthe-art techniques in literature that used the same CoMoFoD dataset and validation metrics to achieve fair comparison. Table 8 presents a comparison of the proposed approach with other popular approaches, namely, HOG [3], HOGM [39], PCET [40], LGWP [41] and Convolutional Kernel Network [42]. The proposed CMFD based on QPCET descriptors provide superior detection efficiency to previous methods.…”

Section: Resultsmentioning

confidence: 99%

Detection Copy-Move Forgery in Image Via Quaternion Polar Harmonic Transforms

2019

KSII TIIS

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Copy-move forgery (CMF) in digital images is a detrimental tampering of artefacts that requires precise detection and analysis. CMF is performed by copying and pasting a part of an image into other portions of it. Despite several efforts to detect CMF, accurate identification of noise, blur and rotated region-mediated forged image areas is still difficult. A novel algorithm is developed on the basis of quaternion polar complex exponential transform (QPCET) to detect CMF and is conducted involving a few steps. Firstly, the suspicious image is divided into overlapping blocks. Secondly, invariant features for each block are extracted using QPCET. Thirdly, the duplicated image blocks are determined using k-dimensional tree (kd-tree) block matching. Lastly, a new technique is introduced to reduce the flat region-mediated false matches. Experiments are performed on numerous images selected from the CoMoFoD database. MATLAB 2017b is used to employ the proposed method. Metrics such as correct and false detection ratios are utilised to evaluate the performance of the proposed CMF detection method. Experimental results demonstrate the precise and efficient CMF detection capacity of the proposed approach even under image distortion including rotation, scaling, additive noise, blurring, brightness, colour reduction and JPEG compression. Furthermore, our method can solve the false match problem and outperform existing ones in terms of precision and false positive rate. The proposed approach may serve as a basis for accurate digital image forensic investigations.

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Section: Resultsmentioning

confidence: 99%

Detection Copy-Move Forgery in Image Via Quaternion Polar Harmonic Transforms

2019

KSII TIIS

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“…Figure 6 shows the performances comparisons between the proposed algorithm and the state-of-the-art algorithms on resisting rotation, scaling and down-sampling transforms. As shown in Figure 6(a1), the anti-rotation performance of the proposed algorithm is a little lower than that of algorithm [7] at precision. However, the recall of the proposed algorithm, as shown in Figure 6(b1), got the best performance.…”

Section: The Performance Comparisons Between the Proposed Algorithm Amentioning

confidence: 91%

“…The main defect of block-based algorithms is the lack of the resisting of the scaling transforms. Wo et al [18] and Emam et al [7] proposed the polar complex exponential transform (PCET) with multi-radius block to extract the feature of each point. But, its efficiency is low.…”

Section: Introductionmentioning

confidence: 99%

A Duplicated Forgery Detection Fusion Algorithm using SIFT and Radial-Harmonic Fourier Moments

Gan¹

2018

IJPE

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This paper proposed an algorithm that fused block-based algorithm (Radial Harmonic Fourier Moments, RHFMs) and SIFT algorithm (Scale Invariant Feature Transform, SIFT) for the duplicated forgery detection, also called copy-move forgery detection. It can effectively detect forgery image. Firstly, the SIFT algorithm is proposed to extract feature points from the pre-processing image. Subsequently, the nearest-neighbor (2NN) test, adaptive Euclidean distance and Random sample consensus (RANSAC) are applied to remove most of the mismatched feature points and get the candidate inlier matches. The affine matrixes based on the RANSAC are obtained by the candidate inlier matches. Then, Radial Harmonic Fourier Moments is proposed to extract invariances of the candidate inlier matches in circle blocks. The propagated criterion is calculated by affine matrix and circular feature of the inlier matches. The Simple Linear Iterative Clustering (SLIC) is presented to segment the host image into texture patches. Like pixel propagating, the circular block is slid in the corresponding texture blocks that the texture blocks contain the corresponding inlier matches to get more corresponding matches. Finally, some geometric image operations, such as dilation, are employed to eliminate the small holes or isolated pixels. A series of experiments showed that the proposed fusion algorithm can achieve superior performances than those of the moment invariant algorithms under various geometric transformations.

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“…The CMFD methods can be roughly divided into three main categories: block-based, keypoint-based and hybrid methods. The block-based methods [3][4][5][6][7][8][9][10][11][12][13] generally extract image features using invariant moment through overlapping block subdivided in rectangular regions. As an alternative to the CMFD, the keypoint-based methods [14][15][16][17][18][19][20][21][22] extract the features from the whole image.…”

Section: Introductionmentioning

confidence: 99%

“…In [11], Polar Cosine Transform (PCT) has been proposed to extract image block features, which could address the rotation problem. Eman et al [12] have proposed Polar Complex Exponential Transform (PCET) to extract the circle block features. However, most of block-based methods have inherent drawbacks.…”

Section: Introductionmentioning

confidence: 99%

Copy-move Forgery Detection Robust to Various Transformation and Degradation Attacks

2018

KSII TIIS

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Trying to deal with the problem of low robustness of Copy-Move Forgery Detection (CMFD) under various transformation and degradation attacks, a novel CMFD method is proposed in this paper. The main advantages of proposed work include: (1) Discrete Analytical Fourier-Mellin Transform (DAFMT) and Locality Sensitive Hashing (LSH) are combined to extract the block features and detect the potential copy-move pairs; (2) The Euclidian distance is incorporated in the pixel variance to filter out the false potential copy-move pairs in the post-verification step. In addition to extracting the effective features of an image block, the DAMFT has the properties of rotation and scale invariance. Unlike the traditional lexicographic sorting method, LSH is robust to the degradations of Gaussian noise and JEPG compression. Because most of the false copy-move pairs locate closely to each other in the spatial domain or are in the homogeneous regions, the Euclidian distance and pixel variance are employed in the post-verification step. After evaluating the proposed method by the precision-recall-F 1 model quantitatively based on the Image Manipulation Dataset (IMD) and Copy-Move Hard Dataset (CMHD), our method outperforms Emam et al.'s and Li et al.'s works in the recall and F 1 aspects.

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PCET based copy-move forgery detection in images under geometric transforms

Cited by 80 publications

References 16 publications

Detection Copy-Move Forgery in Image Via Quaternion Polar Harmonic Transforms

Detection Copy-Move Forgery in Image Via Quaternion Polar Harmonic Transforms

A Duplicated Forgery Detection Fusion Algorithm using SIFT and Radial-Harmonic Fourier Moments

Copy-move Forgery Detection Robust to Various Transformation and Degradation Attacks

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