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Boosting Image Forgery Detection using Resampling Features and Copy-move analysis
[article]
2018
arXiv
pre-print
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We use the copy-move detection method as a pre-filtering step and pass those images that are classified as untampered to a deep learning based resampling detection framework. ...
While resampling detection algorithms are effective in detecting splicing and resampling, copy-move detection algorithms excel in detecting cloning and region removal. ...
The views, opin- His broad research interests include the areas of image processing, computer vision, and video communications and statistical methods for signal analysis. ...
arXiv:1802.03154v2
fatcat:3hfktyx6dbau5bw436d7oykdra
Boosting Image Forgery Detection using Resampling Features and Copy-move Analysis
2018
IS&T International Symposium on Electronic Imaging Science and Technology
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We use the copy-move detection method as a pre-filtering step and pass those images that are classified as untampered to a deep learning based resampling detection framework. ...
While resampling detection algorithms are effective in detecting splicing and resampling, copy-move detection algorithms excel in detecting cloning and region removal. ...
Author Biography His broad research interests include the areas of image processing, computer vision, and video communications and statistical methods for signal analysis. ...
doi:10.2352/issn.2470-1173.2018.07.mwsf-118
fatcat:7k3uikbtwfemxb4ktpn3byaznu
A Survey on Photo Forgery Detection Methods
2018
ITM Web of Conferences
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Passive detection techniques are also split into three branches; image splicing, image retouching, copy-move. Such image forgery detection methods are focus of this paper. ...
Image forgery detection methods can be divided into two extensive groups such as Active methods and Passive (Blind) methods. ...
Increasing in image forensics has given boosting to special techniques for the detection of changing image. ...
doi:10.1051/itmconf/20182201055
fatcat:w5ozpmtzdnbstm6ray7da65g7u
Passive Aproaches for Detecting Image Tampering: A Review
2015
Jurnal Teknologi
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Graphical abstract A picture of a woman superimposed on a fashion-show catwalk stage Abstract This paper defines the presently used methods and approaches in the domain of digital image forgery detection ...
This area of research is relatively new and only a few sources exist that directly relate to the detection of image forgeries. ...
Copy-Move Another common type of image forgery is the copy-move (or region duplication or cloning) forgery. ...
doi:10.11113/jt.v73.4189
fatcat:if7crdr6azhyje3qpkgvbmw5ui
Blind Image Tamper Detection Based on Multimodal Fusion
[chapter]
2010
Lecture Notes in Computer Science
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In this paper, we propose a novel fuzzy fusion of image residue features for detecting tampering or forgery in video sequences. ...
We suggest use of feature selection techniques in conjunction with fuzzy fusion approach to enhance the robustness of tamper detection methods. ...
In this case, the copy move forgery can be successfully detected by a different detector. ...
doi:10.1007/978-3-642-17534-3_69
fatcat:c5ekmirnkfgs7f4qeghslsf4uq
Hybrid LSTM and Encoder-Decoder Architecture for Detection of Image Forgeries
[article]
2019
arXiv
pre-print
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Resampling features are used to capture artifacts like JPEG quality loss, upsampling, downsampling, rotation, and shearing. ...
With advanced image journaling tools, one can easily alter the semantic meaning of an image by exploiting certain manipulation techniques such as copy-clone, object splicing, and removal, which mislead ...
In [48] , the authors used an interesting segmentation based approach to detect copy-move forgeries. ...
arXiv:1903.02495v1
fatcat:bu6iacqbhvbbxboebyfwwu2qne
Exposing Digital Image Forgeries by Detecting Contextual Abnormality Using Convolutional Neural Networks
2020
Sensors
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However, previous methods that employed low-level features are highly vulnerable, even to frequently used image processing techniques such as JPEG and resizing, because these techniques add noise to the ...
Thus, the proposed forensics can detect image forgery based on contextual abnormality as long as the object can be identified even if noise is applied to the image, contrary to methods that employ low-level ...
Another family of forgery is a copy-move modification [9] [10] [11] . In a copy-move forgery, a part of the image itself is copied and pasted into another part of the same image [9] . ...
doi:10.3390/s20082262
pmid:32316220
pmcid:PMC7219587
fatcat:2vwhaugaafg7jcdxggbnoyu474
Image Forgery Detection Using Deeplearning by Recompressing Images
2022
Electronics
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However, most image forgery techniques based on CNN that exist in the literature are limited to detecting a specific type of forgery (either image splicing or copy-move). ...
This increases the severity and frequency of image forgeries, which is now a major source of concern. Numerous traditional techniques have been developed over time to detect image forgeries. ...
Acknowledgments: We are thankful to CNRS for providing us the GPU Cluster Jean Zay (http: //www.idris.fr/jean-zay/ accessed on 10 January 2022) to train our network. ...
doi:10.3390/electronics11030403
fatcat:5l5d4f2lqjatnb2pq3qeuvdqmy
TransForensics: Image Forgery Localization with Dense Self-Attention
[article]
2021
arXiv
pre-print
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To tackle this challenging problem, we introduce TransForensics, a novel image forgery localization method inspired by Transformers. ...
Nowadays advanced image editing tools and technical skills produce tampered images more realistically, which can easily evade image forensic systems and make authenticity verification of images more difficult ...
Splicing means copying regions from an image to another image. Copy-move copies and pastes regions within the same image. Removal means removing regions from the current image. ...
arXiv:2108.03871v1
fatcat:r2bzn53ptbhsbg4d4bo5w2zobq
An Evaluation of Popular Copy-Move Forgery Detection Approaches
2012
IEEE Transactions on Information Forensics and Security
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2012 pre-print arXiv:1208.3665v1 fatcat:avk2utdy6fdavldv6fmnsw5fbuOther Versions
A copy-move forgery is created by copying and pasting content within the same image, and potentially post-processing it. ...
In recent years, the detection of copy-move forgeries has become one of the most actively researched topics in blind image forensics. ...
CONCLUSION We evaluated the performance of different widely-used features for copy-move forgery detection. ...
doi:10.1109/tifs.2012.2218597
fatcat:pzoovl7wcvg3bk4rjvqaobvdxq
A Comprehensive Review of Deep-Learning-Based Methods for Image Forensics
2021
Journal of Imaging
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of computer graphics images and detection of emerging Deepfake images. ...
Furthermore, image forgeries are presently so realistic that it becomes difficult for the naked eye to differentiate between fake and real media. ...
The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results. ...
doi:10.3390/jimaging7040069
pmid:34460519
pmcid:PMC8321383
fatcat:72zd7nyaifhvlgcxv22zztpm4y
A Full-Image Full-Resolution End-to-End-Trainable CNN Framework for Image Forgery Detection
2020
IEEE Access
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In this work, we propose a CNN-based image forgery detection framework which makes decisions based on fullresolution information gathered from the whole image. ...
INDEX TERMS CNN, digital image forensics, forgery detection. 133488 This work is licensed under a Creative Commons Attribution 4.0 License. ...
copy-move forgery detection [5] - [8] . ...
doi:10.1109/access.2020.3009877
fatcat:kvqs5iu7svcklmado3x3z7bony
Media Forensics and DeepFakes: an overview
[article]
2020
arXiv
pre-print
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This review paper aims to present an analysis of the methods for visual media integrity verification, that is, the detection of manipulated images and videos. ...
Software packages freely available on the web allow any individual, without special skills, to create very realistic fake images and videos. ...
Deep learning methods have been also applied to detect copy-move forgeries. ...
arXiv:2001.06564v1
fatcat:b3izh3hcmrae5frbd2bv3tmlgu
Arbitrary-sized Image Training and Residual Kernel Learning: Towards Image Fraud Identification
[article]
2020
arXiv
pre-print
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With the learnt residual kernels and PBGD, the proposed framework achieved the state-of-the-art results in image fraud identification, especially for images with small tampered regions or unseen images ...
Our arbitrary-sized image training method mainly depends on the pseudo-batch gradient descent (PBGD), which bridges the gap between the input batch and the update batch to assure that model updates can ...
Two types of image forgery, copy-move and splicing, are frequent and thus more concerned. ...
arXiv:2005.11043v1
fatcat:htpkey6rsbdrzaspkx4ez3w2da
Splicing forgery detection and the impact of image resolution
2017
2017 9th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)
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After the results were analyzed using statistical analysis, we came to the conclusion that Algorithm 2 performs better than Algorithm 1 in detecting the forged images. ...
We also examine how the examined splicing forgery detection algorithm works on low-resolution images and considered classification algorithms (classifiers). Methods. ...
Secondly I would like to thank "Image Analysis Processing & Protection Group" for providing the partial source code of the algorithm considered to be improved in this thesis. ...
doi:10.1109/ecai.2017.8166431
fatcat:iojwgshyqzaozakkoawj6onrue
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