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Boosting Image Forgery Detection using Resampling Features and Copy-move analysis [article]

Tajuddin Manhar Mohammed, Jason Bunk, Lakshmanan Nataraj, Jawadul H. Bappy, Arjuna Flenner, B.S. Manjunath, Shivkumar Chandrasekaran, Amit K. Roy-Chowdhury, Lawrence Peterson
2018 arXiv   pre-print
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

Tajuddin Manhar Mohammed, Jason Bunk, Lakshmanan Nataraj, Jawadul H. Bappy, Arjuna Flenner, B.S. Manjunath, Shivkumar Chandrasekaran, Amit K. Roy-Chowdhury, Lawrence A. Peterson
2018 IS&T International Symposium on Electronic Imaging Science and Technology  
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

Bilgehan Gurunlu, Serkan Ozturk, C. Cattani, A. Atangana, H. Bulut, Z. Hammouch, H.M. Baskonus, T. Mekkaoui, S. Agoujil
2018 ITM Web of Conferences  
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

Fatma Salman Hashem, Ghazali Sulong
2015 Jurnal Teknologi  
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]

Girija Chetty, Monica Singh, Matthew White
2010 Lecture Notes in Computer Science  
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]

Jawadul H. Bappy, Cody Simons, Lakshmanan Nataraj, B.S. Manjunath, Amit K. Roy-Chowdhury
2019 arXiv   pre-print
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

Haneol Jang, Jong-Uk Hou
2020 Sensors  
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

Syed Sadaf Ali, Iyyakutti Iyappan Ganapathi, Ngoc-Son Vu, Syed Danish Ali, Neetesh Saxena, Naoufel Werghi
2022 Electronics  
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]

Jing Hao and Zhixin Zhang and Shicai Yang and Di Xie and Shiliang Pu
2021 arXiv   pre-print
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

Vincent Christlein, Christian Riess, Johannes Jordan, Corinna Riess, Elli Angelopoulou
2012 IEEE Transactions on Information Forensics and Security  
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

Ivan Castillo Castillo Camacho, Kai Wang
2021 Journal of Imaging  
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

Francesco Marra, Diego Gragnaniello, Luisa Verdoliva, Giovanni Poggi
2020 IEEE Access  
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]

Luisa Verdoliva
2020 arXiv   pre-print
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]

Hongyu Li, Xiaogang Huang, Zhihui Fu, Xiaolin Li
2020 arXiv   pre-print
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

Vishnu Manasa Devagiri, Abbas Cheddad
2017 2017 9th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)  
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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