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Image forensics
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data compression. Compression can remove protections.
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Splicing forgery
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Detectors
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Image splicing, Image forensics,
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Bit rate, Forensics, Forgery, Image edge detection,
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Image forensics, Compression forensics,
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Distinguish photographs of reality from computer graphics.
directed graphs, feature extraction, image classification,
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Image forensics, Forgery detection, Shadow geometry,
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Survey, Forgery Detection. Image tampering detection, Image forgery detection,
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Convolutional neural network, Anti-fraud, Distance metric
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data compression, decoding, image coding, image resolution,
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Watermarks may interfere with the content of the medical image.
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Discrete cosine transform, Doubly stochastic model,
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Videos, Bit rate, Feature extraction, Encoding, Standards,
Quantization (signal), Forensics, Video forensics,
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Passive forensics, Convolution neural network, SSIM,
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2109
Forgery, Training, Authentication, Visualization, Task analysis,
Security, Forensics, Document image, text editing, deep learning
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2112
Image Forgery Detection, Real Image, Pair-wise Learning,
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Subset scanning, Generative models, Synthetic content detection
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2205
Object-based video forgery, Hybrid deep learning,
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MSTA-Net: Forgery Detection by Generating Manipulation Trace Based on
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2207
Faces, Forgery, Videos, Feature extraction, Databases,
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Elsevier DOI
2212
Document forgery, Spectral, Spatial, Spectral-spatial,
Autoencoders, Unsupervised Deep Learning
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Yu, M.M.[Miao-Miao],
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MSFRNet: Two-Stream Deep Forgery Detector via Multi-Scale Feature
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IET-IPR(17), No. 2, 2023, pp. 581-596.
DOI Link
2302
counterfactual causal reasoning, DeepFake detection,
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SNIS: A Signal Noise Separation-Based Network for Post-Processed
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IEEE DOI
2302
Forgery, Location awareness, Semantics, Feature extraction,
Image coding, Blind source separation, Splicing,
post-processed images
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Bi, X.L.[Xiu-Li],
Shang, Y.X.[Yi-Xuan],
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A Versatile Detection Method for Various Contrast Enhancement
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IEEE DOI
2302
Histograms, Forgery, Transform coding, Semantics, Authentication,
Task analysis, Image coding, Global forgery detection,
ZGS
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Deng, X.[Xin],
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IEEE DOI
2302
Faces, Feature extraction, Forgery,
Generative adversarial networks, Probability density function,
non-local similarity
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Chen, T.[Tong],
Li, B.[Bin],
Zeng, J.H.[Jin-Hua],
Learning Traces by Yourself: Blind Image Forgery Localization via
Anomaly Detection With ViT-VAE,
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IEEE DOI
2303
Training, Location awareness, Forgery, Image reconstruction,
Benchmark testing, Anomaly detection, Transformers, transformer
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Fadl, S.[Sondos],
Hosny, K.M.[Khalid M.],
Hammad, M.[Mohamed],
Automatic fake document identification and localization using DE-Net
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Elsevier DOI
2303
Handwriting forgery detection, Addition, Alteration,
Document examination, Forged document, CNN
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Shi, X.Q.[Xiao-Qian],
Li, P.[Ping],
Wu, H.[Hao],
Chen, Q.D.[Qi-Dong],
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A lightweight image splicing tampering localization method based on
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IET-IPR(17), No. 6, 2023, pp. 1883-1892.
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2305
dual-stream network, image tampering localization,
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Liu, Y.Q.[Ya-Qi],
Lv, B.B.[Bin-Bin],
Jin, X.[Xin],
Chen, X.Y.[Xiao-Yu],
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TBFormer: Two-Branch Transformer for Image Forgery Localization,
SPLetters(30), 2023, pp. 623-627.
IEEE DOI
2306
Feature extraction, Transformers, Forgery, Location awareness, Fuses,
Decoding, Convolution, Image forgery localization, two-branch,
hierarchical-feature fusion
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Li, D.[Dong],
Zhu, J.Y.[Jia-Ying],
Wang, M.[Menglu],
Liu, J.W.[Jia-Wei],
Fu, X.[Xueyang],
Zha, Z.J.[Zheng-Jun],
Edge-aware Regional Message Passing Controller for Image Forgery
Localization,
CVPR23(8222-8232)
IEEE DOI
2309
BibRef
Guillaro, F.[Fabrizio],
Cozzolino, D.[Davide],
Sud, A.[Avneesh],
Dufour, N.[Nicholas],
Verdoliva, L.[Luisa],
TruFor: Leveraging All-Round Clues for Trustworthy Image Forgery
Detection and Localization,
CVPR23(20606-20615)
IEEE DOI
2309
BibRef
Shi, Z.[Zenan],
Shen, X.[Xuanjing],
Chen, H.P.[Hai-Peng],
Lyu, Y.[Yingda],
PL-GNet: Pixel Level Global Network for detection and localization of
image forgeries,
SP:IC(119), 2023, pp. 117029.
Elsevier DOI
2310
Image forgery detection and localization, Global network,
Atrous convolution, Decoding net, Encoding net
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Mehrjardi, F.Z.[Fatemeh Zare],
Latif, A.M.[Ali Mohammad],
Zarchi, M.S.[Mohsen Sardari],
Sheikhpour, R.[Razieh],
A survey on deep learning-based image forgery detection,
PR(144), 2023, pp. 109778.
Elsevier DOI
2310
Forgery detection, Deep learning, Inpainting, Copy move,
Splicing, Tampered image, CNN, RNN, R-CNN, Auto-Encoder
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He, D.[Defen],
Jiang, Q.[Qian],
Jin, X.[Xin],
Cheng, Z.[Zien],
Liu, S.[Shuai],
Yao, S.W.[Shao-Wen],
Zhou, W.[Wei],
MCDC-Net: Multi-scale forgery image detection network based on
central difference convolution,
IET-IPR(18), No. 1, 2024, pp. 1-12.
DOI Link
2401
computer vision, convolutional neural nets, convolution,
feature extraction, image processing, image recognition, supervised learning
BibRef
Luo, Y.J.[Yuan-Jing],
Zhou, T.Q.[Tong-Qing],
Cui, S.L.[Sheng-Lan],
Ye, Y.F.[Yun-Fan],
Liu, F.[Fang],
Cai, Z.P.[Zhi-Ping],
Fixing the Double Agent Vulnerability of Deep Watermarking:
A Patch-Level Solution Against Artwork Plagiarism,
CirSysVideo(34), No. 3, March 2024, pp. 1670-1683.
IEEE DOI
2403
Watermarking, Plagiarism, Training, Robustness, Decoding, Distortion,
Copyright protection, Deep watermarking, convolutional neural networks
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Melman, A.[Anna],
Evsutin, O.[Oleg],
Methods for countering attacks on image watermarking schemes:
Overview,
JVCIR(99), 2024, pp. 104073.
Elsevier DOI
2403
Digital images, Watermarking, Robustness, Removal attacks, Forgery attacks
BibRef
Boato, G.[Giulia],
de Natale, F.G.B.[Francesco G.B.],
de Stefano, G.[Gianluca],
Pasquini, C.[Cecilia],
Roli, F.[Fabio],
Adversarial mimicry attacks against image splicing forensics: An
approach for jointly hiding manipulations and creating false
detections,
PRL(179), 2024, pp. 73-79.
Elsevier DOI
2403
Adversarial multimedia forensics, Gray-box attack,
Image manipulation hiding, False forgery creation, Image splicing detection
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Gardella, M.[Marina],
Mus©, P.[Pablo],
Colom, M.[Miguel],
Morel, J.M.[Jean-Michel],
Image Forgery Detection Based on Noise Inspection: Analysis and
Refinement of the Noisesniffer Method,
IPOL(14), 2024, pp. 86-115.
DOI Link
2404
BibRef
Shan, W.Y.[Wu-Yang],
Liu, A.[Aoling],
Qiu, J.[Junying],
Li, J.[Jun],
SLRID: A Robust Image Tampering Localization Framework for Extremely
Scaled Forgery Images,
SPLetters(31), 2024, pp. 2095-2099.
IEEE DOI
2408
Forensics, Location awareness, Wavelet transforms, Detectors,
Transforms, Forgery, Feature extraction, Image forensics, robustness
BibRef
Luo, D.L.[Dong-Liang],
Liu, Y.L.[Yu-Liang],
Yang, R.[Rui],
Liu, X.J.[Xian-Jin],
Zeng, J.[Jishen],
Zhou, Y.[Yu],
Bai, X.[Xiang],
Toward real text manipulation detection: New dataset and new solution,
PR(157), 2025, pp. 110828.
Elsevier DOI Code:
WWW Link.
2409
Tampered text detection, Document forgery, Image forensics,
Image manipulation detection, Multi-modal
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Corvi, R.[Riccardo],
Cozzolino, D.[Davide],
Poggi, G.[Giovanni],
Nagano, K.[Koki],
Verdoliva, L.[Luisa],
Intriguing properties of synthetic images: from generative
adversarial networks to diffusion models,
WMF23(973-982)
IEEE DOI
2309
BibRef
Guo, X.[Xiao],
Liu, X.H.[Xiao-Hong],
Ren, Z.Y.[Zhi-Yuan],
Grosz, S.[Steven],
Masi, I.[Iacopo],
Liu, X.M.[Xiao-Ming],
Hierarchical Fine-Grained Image Forgery Detection and Localization,
CVPR23(3155-3165)
IEEE DOI
2309
BibRef
Niloy, F.F.[Fahim Faisal],
Bhaumik, K.K.[Kishor Kumar],
Woo, S.S.[Simon S.],
CFL-Net: Image Forgery Localization Using Contrastive Learning,
WACV23(4631-4640)
IEEE DOI
2302
Location awareness, Measurement, Fuses, Image edge detection,
Transform coding, Focusing, Benchmark testing, Social good
BibRef
Ma, J.W.[Jing-Wei],
Chai, L.[Lucy],
Huh, M.Y.[Min-Young],
Wang, T.Z.[Tong-Zhou],
Lim, S.N.[Ser-Nam],
Isola, P.[Phillip],
Torralba, A.[Antonio],
Totems: Physical Objects for Verifying Visual Integrity,
ECCV22(XIV:164-180).
Springer DOI
2211
BibRef
Liu, B.[Bo],
Yang, F.[Fan],
Bi, X.L.[Xiu-Li],
Xiao, B.[Bin],
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Gao, X.B.[Xin-Bo],
Detecting Generated Images by Real Images,
ECCV22(XIV:95-110).
Springer DOI
2211
BibRef
Gudavalli, C.[Chandrakanth],
Rosten, E.[Erik],
Nataraj, L.[Lakshmanan],
Chandrasekaran, S.[Shivkumar],
Manjunath, B.S.,
SeeTheSeams: Localized Detection of Seam Carving based Image Forgery
in Satellite Imagery,
WMF22(1-11)
IEEE DOI
2210
Location awareness, Measurement, Satellites, Image coding, Roads
BibRef
Wu, H.W.[Hai-Wei],
Zhou, J.T.[Jian-Tao],
Tian, J.[Jinyu],
Liu, J.[Jun],
Robust Image Forgery Detection over Online Social Network Shared
Images,
CVPR22(13430-13439)
IEEE DOI
2210
Training, Social networking (online), Detectors, Predictive models,
Propagation losses, Forgery, Transparency, fairness, accountability,
Vision applications and systems
BibRef
Das, S.[Sowmen],
Islam, M.S.[Md. Saiful],
Amin, M.R.[Md. Ruhul],
GCA-Net: Utilizing Gated Context Attention for Improving Image
Forgery Localization and Detection,
WMF22(81-90)
IEEE DOI
2210
Location awareness, Training, Semantics, Logic gates,
Benchmark testing, Forgery, Robustness
BibRef
Rao, Y.[Yuan],
Ni, J.Q.[Jiang-Qun],
Self-supervised Domain Adaptation for Forgery Localization of JPEG
Compressed Images,
ICCV21(15014-15023)
IEEE DOI
2203
Location awareness, Image coding, Social networking (online),
Splicing, Transform coding, Computer architecture,
Transfer/Low-shot/Semi/Unsupervised Learning
BibRef
Hao, J.[Jing],
Zhang, Z.X.[Zhi-Xin],
Yang, S.[Shicai],
Xie, D.[Di],
Pu, S.L.[Shi-Liang],
TransForensics: Image Forgery Localization with Dense Self-Attention,
ICCV21(15035-15044)
IEEE DOI
2203
Location awareness, Learning systems, Image forensics, Semantics,
Object detection, Transformers, Solids,
grouping and shape
BibRef
Bammey, Q.[Quentin],
von Gioi, R.G.[Rafael Grompone],
Morel, J.M.[Jean-Michel],
Forgery Detection by Internal Positional Learning of Demosaicing
Traces,
WACV22(1019-1029)
IEEE DOI
2202
Training, Image coding, Image color analysis,
Forensics, Neural networks, Transform coding, Transfer, Few-shot,
Semi- and Un- supervised Learning Image forensics
BibRef
Saire, D.[Darwin],
Tabbone, S.A.[Salvatore A.],
Documents Counterfeit Detection Through a Deep Learning Approach,
ICPR21(3915-3922)
IEEE DOI
2105
Deep learning, Visualization, Image resolution, Neural networks,
Predictive models, Benchmark testing, Feature extraction
BibRef
Jeong, Y.H.[Yong-Hyun],
Choi, J.W.[Jong-Won],
Kim, D.[Doyeon],
Park, S.[Sehyeon],
Hong, M.[Minki],
Park, C.H.[Chang-Hyun],
Min, S.[Seungjai],
Gwon, Y.[Youngjune],
Dofnet: Depth of Field Difference Learning for Detecting Image Forgery,
ACCV20(VI:83-100).
Springer DOI
2103
BibRef
Bai, Y.,
Guo, Y.,
Wei, J.,
Lu, L.,
Wang, R.,
Wang, Y.,
Fake Generated Painting Detection Via Frequency Analysis,
ICIP20(1256-1260)
IEEE DOI
2011
Painting, Feature extraction, Frequency-domain analysis, Databases,
Testing, Forgery, Support vector machines, Image Forgery Detection,
Fourier Transform
BibRef
Qian, Y.Y.[Yu-Yang],
Yin, G.J.[Guo-Jun],
Sheng, L.[Lu],
Chen, Z.X.[Zi-Xuan],
Shao, J.[Jing],
Thinking in Frequency: Face Forgery Detection by Mining Frequency-aware
Clues,
ECCV20(XII: 86-103).
Springer DOI
2010
BibRef
Wang, T.[Tao],
Du, M.[Maggie],
Wu, X.M.[Xin-Min],
He, T.P.[Tai-Ping],
An Analytical Framework for Trusted Machine Learning and Computer
Vision Running with Blockchain,
TCV20(32-38)
IEEE DOI
2008
How to trust the results.
Machine learning, Computational modeling, Servers,
Contracts, Automation
BibRef
Kumar, A.,
Bhavsar, A.,
Verma, R.,
Syn2Real: Forgery Classification via Unsupervised Domain Adaptation,
WACVWS20(63-70)
IEEE DOI
2006
Forgery, Feature extraction, Semantics, Image edge detection,
Task analysis, Adaptation models, Splicing
BibRef
Li, H.,
Huang, J.,
Localization of Deep Inpainting Using High-Pass Fully Convolutional
Network,
ICCV19(8300-8309)
IEEE DOI
2004
convolutional neural nets, feature extraction,
image classification, image filtering, image recognition,
Probability
BibRef
Wu, Y.[Yue],
AbdAlmageed, W.[Wael],
Natarajan, P.[Premkumar],
ManTra-Net: Manipulation Tracing Network for Detection and Localization
of Image Forgeries With Anomalous Features,
CVPR19(9535-9544).
IEEE DOI
2002
Code:
See also Analysis and Experimentation on the ManTraNet Image Forgery Detector.
BibRef
McCloskey, S.,
Albright, M.,
Detecting GAN-Generated Imagery Using Saturation Cues,
ICIP19(4584-4588)
IEEE DOI
1910
BibRef
Jenni, S.[Simon],
Favaro, P.[Paolo],
Self-Supervised Feature Learning by Learning to Spot Artifacts,
CVPR18(2733-2742)
IEEE DOI
1812
Real images vs. synthetic.
Maintenance engineering, Decoding, Task analysis, Training,
Feature extraction, Image segmentation
BibRef
Roy, A.,
Tariang, D.B.,
Chakraborty, R.S.,
Naskar, R.,
Discrete Cosine Transform Residual Feature Based Filtering Forgery
and Splicing Detection in JPEG Images,
PRIV18(1633-16338)
IEEE DOI
1812
Discrete cosine transforms, Feature extraction, Forgery, Splicing,
Transform coding, Histograms, Forensics
BibRef
Privman-Horesh, N.,
Haider, A.,
Hel-Or, H.,
Forgery Detection in 3D-Sensor Images,
PRIV18(1642-16428)
IEEE DOI
1812
Cameras, Forgery, Sensors, Lighting
BibRef
Artaud, C.,
Sidčre, N.,
Doucet, A.,
Ogier, J.,
Yooz, V.P.D.,
Find it! Fraud Detection Contest Report,
ICPR18(13-18)
IEEE DOI
1812
Task analysis, Forgery, Tools, XML, Companies,
Optical character recognition software, Training
BibRef
Zhang, Z.,
Zhang, Y.,
Zhou, Z.,
Luo, J.,
Boundary-based Image Forgery Detection by Fast Shallow CNN,
ICPR18(2658-2663)
IEEE DOI
1812
Forgery, Image edge detection, Image resolution,
Feature extraction, Image coding, Signal processing
BibRef
Kuznetsov, A.[Andrey],
Camera Sensor Traces Analysis in Image Forgery Detection Problem,
ICCVG18(453-463).
Springer DOI
1810
BibRef
Maigrot, C.,
Kijak, E.,
Claveau, V.,
Context-Aware Forgery Localization in Social-Media Images: A
Feature-Based Approach Evaluation,
ICIP18(545-549)
IEEE DOI
1809
Social network services, Splicing, Forgery, Kernel, Estimation,
Image forensics, Measurement, Forgery localization,
Image tampering
BibRef
Long, C.,
Smith, E.,
Basharat, A.,
Hoogs, A.,
A C3D-Based Convolutional Neural Network for Frame Dropping Detection
in a Single Video Shot,
MedForen17(1898-1906)
IEEE DOI
1709
Cameras, Color, Feature extraction, Forgery, Histograms,
Support vector machines, Training
BibRef
Bunk, J.,
Bappy, J.H.,
Mohammed, T.M.,
Nataraj, L.,
Flenner, A.,
Manjunath, B.S.,
Chandrasekaran, S.,
Roy-Chowdhury, A.K.,
Peterson, L.,
Detection and Localization of Image Forgeries Using Resampling
Features and Deep Learning,
MedForen17(1881-1889)
IEEE DOI
1709
Feature extraction, Heating systems, Image segmentation,
Machine learning, Neural networks, Radon, Transform, coding
BibRef
Zhou, J.H.[Jiang-Hong],
Ni, J.Q.[Jiang-Qun],
Rao, Y.[Yuan],
Block-Based Convolutional Neural Network for Image Forgery Detection,
IWDW17(65-76).
Springer DOI
1708
BibRef
Vieira, R.[Rafael],
Antunes, M.[Mário],
Silva, C.[Catarina],
Assis, A.[Ana],
Automatic Documents Counterfeit Classification Using Image Processing
and Analysis,
IbPRIA17(400-407).
Springer DOI
1706
BibRef
Cattaneo, G.[Giuseppe],
Roscigno, G.[Gianluca],
Bruno, A.[Andrea],
Using PNU-Based Techniques to Detect Alien Frames in Videos,
ACIVS16(735-746).
Springer DOI
1611
Apply techniques like in camera id
BibRef
Luo, Z.[Zhipei],
Shafait, F.[Faisal],
Mian, A.[Ajmal],
Localized forgery detection in hyperspectral document images,
ICDAR15(496-500)
IEEE DOI
1511
BibRef
Cattaneo, G.[Giuseppe],
Ferraro Petrillo, U.,
Roscigno, G.[Gianluca],
de Fusco, C.,
A PNU-based technique to detect forged regions in digital images,
ACIVS15(486-498)
Springer DOI
1611
BibRef
Julliand, T.[Thibault],
Nozick, V.[Vincent],
Talbot, H.[Hugues],
Automatic Image Splicing Detection Based on Noise Density Analysis in
Raw Images,
ACIVS16(126-134).
Springer DOI
1611
BibRef
Buchana, P.,
Cazan, I.,
Diaz-Granados, M.,
Juefei-Xu, F.,
Savvides, M.,
Simultaneous forgery identification and localization in paintings
using advanced correlation filters,
ICIP16(146-150)
IEEE DOI
1610
Art
BibRef
Mathai, M.,
Rajan, D.,
Emmanuel, S.,
Video forgery detection and localization using normalized
cross-correlation of moment features,
Southwest16(149-152)
IEEE DOI
1605
Computers
BibRef
Zheng, L.[Lu],
Sun, T.[Tanfeng],
Shi, Y.Q.[Yun-Qing],
Inter-frame Video Forgery Detection Based on Block-Wise Brightness
Variance Descriptor,
IWDW14(18-30).
Springer DOI
1602
BibRef
Wang, W.[Wan],
Jiang, X.H.[Xing-Hao],
Wang, S.L.[Shi-Lin],
Wan, M.[Meng],
Sun, T.F.[Tan-Feng],
Identifying Video Forgery Process Using Optical Flow,
IWDW13(244-257).
Springer DOI
1407
BibRef
Lin, X.F.[Xu-Feng],
Li, C.T.[Chang-Tsun],
Hu, Y.J.[Yong-Jian],
Exposing image forgery through the detection of contrast enhancement,
ICIP13(4467-4471)
IEEE DOI
1402
Digital forensics
BibRef
Saleh, S.Q.[Sahar Q.],
Hussain, M.[Muhammad],
Muhammad, G.[Ghulam],
Bebis, G.N.[George N.],
Evaluation of Image Forgery Detection Using Multi-scale Weber Local
Descriptors,
ISVC13(II:416-424).
Springer DOI
1311
BibRef
Cozzolino, D.[Davide],
Gargiulo, F.[Francesco],
Multiple Classifier Systems for Image Forgery Detection,
CIAP13(II:259-268).
Springer DOI
1309
BibRef
Cozzolino, D.[Davide],
Poggi, G.[Giovanni],
Sansone, C.[Carlo],
Verdoliva, L.[Luisa],
A Comparative Analysis of Forgery Detection Algorithms,
SSSPR12(693-700).
Springer DOI
1211
BibRef
Zach, F.[Fabian],
Riess, C.[Christian],
Angelopoulou, E.[Elli],
Automated Image Forgery Detection through Classification of Jpeg Ghosts,
DAGM12(185-194).
Springer DOI
1209
BibRef
Al-Hammadi, M.H.[Muneer H.],
Muhammad, G.[Ghulam],
Hussain, M.[Muhammad],
Bebis, G.N.[George N.],
Curvelet Transform and Local Texture Based Image Forgery Detection,
ISVC13(II:503-512).
Springer DOI
1311
BibRef
Polatkan, G.[Gungor],
Jafarpour, S.[Sina],
Brasoveanu, A.[Andrei],
Hughes, S.[Shannon],
Daubechies, I.[Ingrid],
Detection of forgery in paintings using supervised learning,
ICIP09(2921-2924).
IEEE DOI
0911
Not through watermarks, but forgery detection.
BibRef
Zheng, J.B.[Jiang-Bin],
Liu, M.[Miao],
A Digital Forgery Image Detection Algorithm Based on Wavelet
Homomorphic Filtering,
DW08(152-160).
Springer DOI
0811
BibRef
Li, Z.[Zhe],
Zheng, J.B.[Jiang-Bin],
Blind Detection of Digital Forgery Image Based on the Local Entropy of
the Gradient,
DW08(161-169).
Springer DOI
0811
BibRef
Luo, W.Q.[Wei-Qi],
Huang, J.W.[Ji-Wu],
Qiu, G.P.[Guo-Ping],
A Novel Method for Block Size Forensics Based on Morphological
Operations,
DW08(229-239).
Springer DOI
0811
BibRef
Earlier:
Robust Detection of Region-Duplication Forgery in Digital Image,
ICPR06(IV: 746-749).
IEEE DOI
0609
BibRef
Guo, J.H.K.[Jin-Hong Katherine],
Forgery Detection by Local Correspondence,
UMD--TR4122, April 2000.
WWW Link.
BibRef
0004
Guo, J.K.,
Doermann, D.S.,
Rosenfeld, A.,
Off-line Skilled Forgery Detection Using Stroke and Substroke
Properties,
ICPR00(Vol II: 355-358).
IEEE DOI
0009
BibRef
Earlier:
Local Correspondence for Detecting Random Forgeries,
ICDAR97(319-323).
IEEE DOI
9708
BibRef
Chapter on OCR, Document Analysis and Character Recognition Systems continues in
Tamper Detection, Image Manipulation Detection, Forensics .