An Improved Lexicographical Sort Algorithm of Copy-move Forgery Detection

Hu, Jie; Zhang, Huaxiong; Qiang, Gao; Huang, Hai

doi:10.1109/icndc.2011.12

Cited by 34 publications

(14 citation statements)

References 2 publications

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“…To reduce the r matching blocks Jie Hu developed a method distance of Eigen vectors instead of DCT coeffi the block [8]. Yang Wang, Kaitlyn Gurule, Ja Jun Zhengpropose a wavelet based copy m detection and applied multi-level 2D DWT, si approach gives significant results for perceivin forgery [9].…”

Section: Literature Reviewmentioning

confidence: 99%

Copy move forgery detection

Patankar¹,

Sukhpal²,

Shetye³

et al. 2016

International Conference &Amp; Workshop on Electronics &Amp; Telecommunication Engineering (ICWET 2016)

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In the technique of copy move forgery, a certain portion of the digital image is copied and pasted into the same image, in order to hide this target portion. The tampered image looks very much original, since the target region despite being forged, has inherited the basic characteristics of the same image itself. Thus the detection for such kind of forgery is pretty difficult. This paper proposes a method to detect such forged regions using Hybrid Wavelet Transform. The combination of transforms used for the same is of Kekre Wavelet Transform and Hadamard Transform. The Hybrid Transform obtained is then applied to even order overlapping blocks, and the features extracted from each block are then compared with features of all other blocks. For the same image, the overlapping block sizes are varied and a subjective selection is done from the results obtained for each block size.

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Section: Literature Reviewmentioning

confidence: 99%

Copy move forgery detection

Patankar¹,

Sukhpal²,

Shetye³

et al. 2016

International Conference &Amp; Workshop on Electronics &Amp; Telecommunication Engineering (ICWET 2016)

View full text Add to dashboard Cite

show abstract

“…Additionally, codebooks can be designed to offer robustness against stream symbol reception errors. For instance, the lexicographical distance between words can be maximized [16], to limit the probability that an erroneously received word will be treated as another valid one. Model checking techniques can study the effects of such events [17], subsequently proposing protocol revisions as needed.…”

Section: A Research Directionsmentioning

confidence: 99%

BitSurfing: Wireless Communications with Outsourced Symbol Generation

Tsioliaridou

Liaskos

Ioannidis

2018

2018 IEEE 23rd International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD)

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Nano-IoT enables a wide range of ground-breaking technologies, but face implementation challenges due to the extremity of the scale. Space restrictions pose severe power supply considerations, to the point where just a few packet transmissions are sufficient to deplete state-of-the-art supplies. In turn, this translates to difficulties in developing efficient protocols even for basic operations, such as addressing and routing. The present work proposes a new network adapter architecture that can address these challenges. The BitSurfing adapter does not generate packets and, hence, abolishes the need for the corresponding transmission circuitry and power consumption. Instead, it relies on an external symbol generator. The BitSurfing adapter reads incoming symbols, waiting for intended messages to appear in the symbol stream. A short (1-bit), low-energy pulse is then emitted to notify neighboring nodes. BitSurfing adapters are shown to exhibit perpetual (and even battery-less) operation, ability to operate without medium access control, while being completely transparent to applications. Moreover, their operation is event-driven, allowing for clock-less implementations. The new adapters are evaluated in a simulated multi-hop nano-IoT network and are shown to offer nearly-perfect packet delivery rates and practically no collisions, under any congestion level.

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“…Forensic methods should detect duplicated regions even when the copied regions have experienced geometrical distortions such as rotation or scaling. To test the ability of the proposed method to detect copy-move forgery in the presence of such geometrical distortions, we rotated copied regions in test dataset by 2,4,6,8,10,20,60,88,90,92,176,178, and 180 degrees. We assumed this is a reasonable range for practical tampering and scenarios.…”

Section: Rotation and Scalingmentioning

confidence: 99%

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

Jenadeleh

Moghaddam

2016

Journal of Forensic Sciences

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Digital image forgery detection is important because of its wide use in applications such as medical diagnosis, legal investigations, and entertainment. Copy-move forgery is one of the famous techniques, which is used in region duplication. Many of the existing copy-move detection algorithms cannot effectively blind detect duplicated regions that are made by powerful image manipulation software like Photoshop. In this study, a new method is proposed for blind detecting manipulations in digital images based on modified fractal coding and feature vector matching. The proposed method not only detects typical copy-move forgery, but also finds multiple copied forgery regions for images that are subjected to rotation, scaling, reflection, and a mixture of these postprocessing operations. The proposed method is robust against tampered images undergoing attacks such as Gaussian blurring, contrast scaling, and brightness adjustment. The experimental results demonstrated the validity and efficiency of the method.

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An Improved Lexicographical Sort Algorithm of Copy-move Forgery Detection

Cited by 34 publications

References 2 publications

Copy move forgery detection

Copy move forgery detection

BitSurfing: Wireless Communications with Outsourced Symbol Generation

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

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