A survey on image tampering and its detection in real-world photos

Zheng, Lilei; Zhang, Ying; Thing, Vrizlynn L. L.

doi:10.1016/j.jvcir.2018.12.022

Cited by 126 publications

(98 citation statements)

References 87 publications

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“…JPEG compression makes tampering detection of an image difficult. However, some traces of tampering are left behind or distributed across the entire image that can be manipulated in the detection process [9]. Techniques such as double JPEG, JPEG blocks and JPEG quantization are exploited for detection in compressed images 4.…”

Section: Various Passive Methods Are Implemented To Negate the Image mentioning

confidence: 99%

Improved Image Splicing Forgery Detection by Combination of Conformable Focus Measures and Focus Measure Operators Applied on Obtained Redundant Discrete Wavelet Transform Coefficients

et al. 2019

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The image is the best information carrier in the current digital era and the easiest to manipulate. Image manipulation causes the integrity of this information carrier to be ambiguous. The image splicing technique is commonly used to manipulate images by fusing different regions in one image. Over the last decade, it has been confirmed that various structures in science and engineering can be demonstrated more precisely by fractional calculus using integrals or derivative operators. Many fractional-order-based techniques have been used in the image-processing field. Recently, a new specific fractional calculus, called conformable calculus, was delivered. Herein, we employ the combination of conformable focus measures (CFMs), and focus measure operators (FMOs) in obtaining redundant discrete wavelet transform (RDWT) coefficients for improving the image splicing forgery detection. The process of image splicing disorders the content of tampered image and causes abnormality in the image features. The spliced region’s boundaries are usually blurring to avoid detection. To make use of the blurred information, both CFMs and FMOs are used to calculate the degree of blurring of the tampered region’s boundaries for image splicing detection. The two public image datasets IFS-TC and CASIA TIDE V2 are used for evaluation of the proposed method. The obtained results of the proposed method achieved accuracy rate 98.30% for Cb channel on IFS-TC image dataset and 98.60% of the Cb channel on CASIA TIDE V2 with 24-D feature vector. The proposed method exhibited superior results compared with other image splicing detection methods.

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Section: Various Passive Methods Are Implemented To Negate the Image mentioning

confidence: 99%

Improved Image Splicing Forgery Detection by Combination of Conformable Focus Measures and Focus Measure Operators Applied on Obtained Redundant Discrete Wavelet Transform Coefficients

et al. 2019

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“…In Figure 3, a keypoint kA has been moved to kB. For a correct match, kA and kB should be matched by Equation (2). However, the keypoint kB is detected as the potentially matched keypoint with kA because kB has the closest distance (d1,A = 0.2684) to kA.…”

Section: Matchingmentioning

confidence: 99%

“…Because the copied portion of an image is generally scaled or rotated, it is difficult to verify the authenticity of the image based on visual inspection alone. For this reason, the development of reliable copy-move forgery detection (CMFD) methods has become an important issue [1][2][3]. The common framework of CMFD comprises five steps: preprocessing (optional), feature extraction, matching, false match removal, and localization.…”

Section: Introductionmentioning

confidence: 99%

Copy-Move Forgery Detection Using Scale Invariant Feature and Reduced Local Binary Pattern Histogram

et al. 2020

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Because digitized images are easily replicated or manipulated, copy-move forgery techniques are rendered possible with minimal expertise. Furthermore, it is difficult to verify the authenticity of images. Therefore, numerous efforts have been made to detect copy-move forgeries. In this paper, we present an improved region duplication detection algorithm based on the keypoints. The proposed algorithm utilizes the scale invariant feature transform (SIFT) and the reduced local binary pattern (LBP) histogram. The LBP values with 256 levels are obtained from the local window centered at the keypoint, which are then reduced to 10 levels. For a keypoint, a 138-dimensional is generated to detect copy-move forgery. We test the proposed algorithm on various image datasets and compare the detection accuracy with those of existing methods. The experimental results demonstrate that the performance of the proposed scheme is superior to that of other tested copy-move forgery detection methods. Furthermore, the proposed method exhibits a uniform detection performance for various types of test datasets.

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“…The tamperproof and anti-theft for multimedia information mainly rely on tamper detection or adjusting attackers and defenders' payoff. In [13], researchers summarized the typical image tamper types, published image tamper data sets, and recent tamper detection methods. In [14], the location privacy protection scheme based on the routing protocol was proposed to prevent information leakage.…”

Section: Introductionmentioning

confidence: 99%

Privacy Protection: An Anti-Fraud Scheme Based on Improved Bayesian Game Model in Multimedia Communication System

et al. 2020

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In the multimedia communication system, users are often exposed to fraud information from malicious applications (such as providing fake bids and false content), which can easily cause privacy leakage. And multimedia information pluralism make it more difficult to protect users' privacy. To solve these problems, this article proposed an anti-fraud scheme based on improved Bayesian game model. First, we designed a Bargain-bayesian game model for modeling the interaction between applications and regular users. We used the Two-round bargain method to establish payoff matrix for two players and adjust it through regular user's detection rate dynamically. Then we obtained the application's best bid in the first round of bargain by backward induction to prevent malicious applications from sending fake bids. Second, we customized a group of test users and developed another interaction model between applications and users (i.e., regular and test) as the Two-side Bayesian game model based on sliding adaptive logistic regression method, then we put three influencing factors into the payoff matrix: test user's ratio, malicious application's ratio, and regular user's ratio. Through Bayesian Nash Equilibria analysis, we obtained values of three influencing factors when malicious applications provide true content, and thus solved the problem of malicious applications providing false content. Finally, experiment results proved that the new scheme had effectively raised expected payoffs for both players and their transaction achievement rate, and lowered the probability of users being deceived by malicious applications, which successfully solved the issue of users' privacy disclosure.

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A survey on image tampering and its detection in real-world photos

Cited by 126 publications

References 87 publications

Improved Image Splicing Forgery Detection by Combination of Conformable Focus Measures and Focus Measure Operators Applied on Obtained Redundant Discrete Wavelet Transform Coefficients

Improved Image Splicing Forgery Detection by Combination of Conformable Focus Measures and Focus Measure Operators Applied on Obtained Redundant Discrete Wavelet Transform Coefficients

Copy-Move Forgery Detection Using Scale Invariant Feature and Reduced Local Binary Pattern Histogram

Privacy Protection: An Anti-Fraud Scheme Based on Improved Bayesian Game Model in Multimedia Communication System

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