25.3.11.4 Copy-Move Tamper Detection, Splicing, Forensics

Chapter Contents (Back)
Copy Move. Splice. Tamper Detection. Image Forensics. Forgery Detection. Cut and paste

Jajal, B.[Brijesh], Desai, V.[Vipul],
Identification of copy-paste regions in digital image,
IJIST(20), No. 4, December 2010, pp. 367-369.
DOI Link 1011
Image forensics. BibRef

Lyu, S.W.[Si-Wei], Pan, X.[Xunyu], Zhang, X.[Xing],
Exposing Region Splicing Forgeries with Blind Local Noise Estimation,
IJCV(110), No. 1, November 2014, pp. 202-221.
WWW Link. 1411
BibRef
Earlier: A2, A3, A1:
Exposing image splicing with inconsistent local noise variances,
ICCP12(1-10).
IEEE DOI 1208
BibRef

Silva, E.[Ewerton], Carvalho, T.[Tiago], Ferreira, A.[Anselmo], Rocha, A.[Anderson],
Going deeper into copy-move forgery detection: Exploring image telltales via multi-scale analysis and voting processes,
JVCIR(29), No. 1, 2015, pp. 16-32.
Elsevier DOI 1504
Award, JVCI. Copy-move forgery detection BibRef

Lee, J.C.[Jen-Chun],
Copy-move image forgery detection based on Gabor magnitude,
JVCIR(31), No. 1, 2015, pp. 320-334.
Elsevier DOI 1508
Digital image forensics BibRef

Ferreira, A., Felipussi, S.C., Alfaro, C., Fonseca, P., Vargas-Muńoz, J.E., dos Santos, J.A., Rocha, A.,
Behavior Knowledge Space-Based Fusion for Copy-Move Forgery Detection,
IP(25), No. 10, October 2016, pp. 4729-4742.
IEEE DOI 1610
decision making BibRef

Dixit, R.[Rahul], Naskar, R.[Ruchira], Mishra, S.[Swati],
Blur-invariant copy-move forgery detection technique with improved detection accuracy utilising SWT-SVD,
IET-IPR(11), No. 5, April 2017, pp. 301-309.
DOI Link 1706
BibRef

Dixit, R.[Rahul], Naskar, R.[Ruchira],
Review, analysis and parameterisation of techniques for copy-move forgery detection in digital images,
IET-IPR(11), No. 9, September 2017, pp. 746-759.
DOI Link 1709
BibRef

Warif, N.B.A.[Nor Bakiah Abdul], Wahab, A.W.A.[Ainuddin Wahid Abdul], Idris, M.Y.I.[M. Yamani Idna], Salleh, R.[Rosli], Othman, F.[Fazidah],
SIFT-Symmetry: A robust detection method for copy-move forgery with reflection attack,
JVCIR(46), No. 1, 2017, pp. 219-232.
Elsevier DOI 1706
Blind, detection BibRef

Jin, G.N.[Guo-Nian], Wan, X.X.[Xiao-Xia],
An improved method for SIFT-based copy-move forgery detection using non-maximum value suppression and optimized J-Linkage,
SP:IC(57), No. 1, 2017, pp. 113-125.
Elsevier DOI 1709
Copy-move forgery detection BibRef

Soni, B.[Badal], Das, P.K.[Pradip K.], Thounaojam, D.M.[Dalton Meitei],
CMFD: a detailed review of block based and key feature based techniques in image copy-move forgery detection,
IET-IPR(12), No. 2, February 2018, pp. 167-178.
DOI Link 1801
BibRef

Wo, Y.[Yan], Yang, K.M.[Ke-Min], Han, G.Q.[Guo-Qiang], Chen, H.C.[Hai-Chao], Wu, W.B.[Wen-Bo],
Copy-move forgery detection based on multi-radius PCET,
IET-IPR(11), No. 2, February 2017, pp. 99-108.
DOI Link 1703
BibRef

Manu, V.T., Mehtre, B.M.,
Copy-move tampering detection using affine transformation property preservation on clustered keypoints,
SIViP(12), No. 3, March 2018, pp. 549-556.
WWW Link. 1804
BibRef

Mahmood, T.[Toqeer], Mehmood, Z.[Zahid], Shah, M.[Mohsin], Saba, T.[Tanzila],
A robust technique for copy-move forgery detection and localization in digital images via stationary wavelet and discrete cosine transform,
JVCIR(53), 2018, pp. 202-214.
Elsevier DOI 1805
Copy-move forgery, Tampered images, Forgery detection, Authenticity, Passive authentication BibRef

Bi, X.L.[Xiu-Li], Pun, C.M.[Chi-Man],
Fast copy-move forgery detection using local bidirectional coherency error refinement,
PR(81), 2018, pp. 161-175.
Elsevier DOI 1806
Copy-move forgery detection, Enhanced coherency sensitive searching, Local bidirectional coherency error BibRef

Liu, B.[Bo], Pun, C.M.[Chi-Man],
Locating splicing forgery by fully convolutional networks and conditional random field,
SP:IC(66), 2018, pp. 103-112.
Elsevier DOI 1806
Splicing forgery, Deep neural network, Fully convolutional network, Conditional random field BibRef

Barni, M., Santoyo-García, H., Tondi, B.,
An Improved Statistic for the Pooled Triangle Test Against PRNU-Copy Attack,
SPLetters(25), No. 10, October 2018, pp. 1435-1439.
IEEE DOI 1810
cameras, image forensics, security of data, statistical analysis, pooled triangle test, PRNU-copy attack, triangle test BibRef

Soni, B.[Badal], Das, P.K.[Pradip K.], Thounaojam, D.M.[Dalton Meitei],
Keypoints based enhanced multiple copy-move forgeries detection system using density-based spatial clustering of application with noise clustering algorithm,
IET-IPR(12), No. 11, November 2018, pp. 2092-2099.
DOI Link 1810
BibRef

d'Amiano, L., Cozzolino, D., Poggi, G., Verdoliva, L.,
A PatchMatch-Based Dense-Field Algorithm for Video Copy-Move Detection and Localization,
CirSysVideo(29), No. 3, March 2019, pp. 669-682.
IEEE DOI 1903
Forgery, Feature extraction, Data structures, Boolean functions, Additives, Complexity theory, Tools, Video forensics, 3D PatchMatch BibRef

Fanfani, M.[Marco], Bellavia, F.[Fabio], Iuliani, M.[Massimo], Piva, A.[Alessandro], Colombo, C.[Carlo],
FISH: Face intensity-shape histogram representation for automatic face splicing detection,
JVCIR(63), 2019, pp. 102586.
Elsevier DOI 1909
Image forensics, Scene level analysis, Geometric constraints, Lighting environment, Face splicing detection BibRef

Fanfani, M.[Marco], Iuliani, M.[Massimo], Bellavia, F.[Fabio], Colombo, C.[Carlo], Piva, A.[Alessandro],
A vision-based fully automated approach to robust image cropping detection,
SP:IC(80), 2020, pp. 115629.
Elsevier DOI 1912
Multimedia forensics, Robust Cropping detection, Image content analysis BibRef

Selvaraj, P.[Priyadharsini], Karuppiah, M.[Muneeswaran],
Enhanced copy-paste forgery detection in digital images using scale-invariant feature transform,
IET-IPR(14), No. 3, 28 February 2020, pp. 462-471.
DOI Link 2002
BibRef

Tian, X.[Xiuxia], Zhou, G.[Guoshuai], Xu, M.[Man],
Image copy-move forgery detection algorithm based on ORB and novel similarity metric,
IET-IPR(14), No. 10, August 2020, pp. 2092-2100.
DOI Link 2008
BibRef

Hajialilu, S.F.[Somayeh Fatan], Azghani, M.[Masoumeh], Kazemi, N.[Neda],
Image copy-move forgery detection using sparse recovery and keypoint matching,
IET-IPR(14), No. 12, October 2020, pp. 2799-2807.
DOI Link 2010
BibRef

Tinnathi, S.[Sreenivasu], Sudhavani, G.,
An efficient copy move forgery detection using adaptive watershed segmentation with AGSO and hybrid feature extraction,
JVCIR(74), 2021, pp. 102966.
Elsevier DOI 2101
Copy-move forgery detection, Segments, Adaptive Galactic Swarm Optimization, RANSAC, Adaptive thresholding BibRef

Aloraini, M., Sharifzadeh, M., Schonfeld, D.,
Sequential and Patch Analyses for Object Removal Video Forgery Detection and Localization,
CirSysVideo(31), No. 3, March 2021, pp. 917-930.
IEEE DOI 2103
Forgery, Analytical models, Video sequences, Correlation, Spatiotemporal phenomena, Feature extraction, object removal video forgery BibRef

Dixit, A.[Anuja], Bag, S.[Soumen],
Composite attacks-based copy-move image forgery detection using AKAZE and FAST with automatic contrast thresholding,
IET-IPR(14), No. 17, 24 December 2020, pp. 4528-4542.
DOI Link 2104
BibRef

Lyu, Q.Y.[Qi-Yue], Luo, J.W.[Jun-Wei], Liu, K.[Ke], Yin, X.L.[Xiao-Lin], Liu, J.R.[Jia-Rui], Lu, W.[Wei],
Copy Move Forgery Detection based on double matching,
JVCIR(76), 2021, pp. 103057.
Elsevier DOI 2104
Digital forensics, Copy move forgery detection, Delaunay triangle, Double matching BibRef

Niu, P., Wang, C., Chen, W., Yang, H., Wang, X.,
Fast and effective Keypoint-based image copy-move forgery detection using complex-valued moment invariants,
JVCIR(77), 2021, pp. 103068.
Elsevier DOI 2106
Copy-move forgery detection, Complex-valued moment invariants, Magnitude-phase hierarchical matching, Adaptive clustering, Two-stage false matches filtering BibRef

Diwan, A.[Anjali], Sharma, R.[Rajat], Roy, A.K.[Anil K.], Mitra, S.K.[Suman K.],
Keypoint based comprehensive copy-move forgery detection,
IET-IPR(15), No. 6, 2021, pp. 1298-1309.
DOI Link 2106
BibRef

Goel, N.[Nidhi], Kaur, S.[Samarjeet], Bala, R.[Ruchika],
Dual branch convolutional neural network for copy move forgery detection,
IET-IPR(15), No. 3, 2021, pp. 656-665.
DOI Link 2106
BibRef

Chalamalasetty, S.P.[Sai Pratheek], Giduturi, S.R.[Srinivasa Rao],
Research Perception Towards Copy-Move Image Forgery Detection: Challenges and Future Directions,
IJIG(21), No. 4, October 2021 2021, pp. 2150054.
DOI Link 2110
BibRef

Chen, B.J.[Bei-Jing], Tan, W.J.[Wei-Jin], Coatrieux, G.[Gouenou], Zheng, Y.H.[Yu-Hui], Shi, Y.Q.[Yun-Qing],
A Serial Image Copy-Move Forgery Localization Scheme With Source/Target Distinguishment,
MultMed(23), 2021, pp. 3506-3517.
IEEE DOI 2110
Convolution, Feature extraction, Forgery, Correlation, Standards, Task analysis, Decoding, Copy-move, image forgery, attention mechanism BibRef

Liu, Y.Q.[Ya-Qi], Xia, C.[Chao], Zhu, X.B.[Xia-Bin], Xu, S.W.[Sheng-Wei],
Two-Stage Copy-Move Forgery Detection With Self Deep Matching and Proposal SuperGlue,
IP(31), 2022, pp. 541-555.
IEEE DOI 2112
Proposals, Feature extraction, Forgery, Convolution, Visualization, Transforms, Task analysis, Image forensics, proposal SuperGlue BibRef

Chen, Y.L.[Yan-Li], Retraint, F.[Florent], Qiao, T.[Tong],
Image splicing forgery detection using simplified generalized noise model,
SP:IC(107), 2022, pp. 116785.
Elsevier DOI 2208
Image splicing detection, Noise model, Camera fingerprints, Hypothesis testing BibRef

Ganeshan, R., Muppidi, S.[Satish], Thirupurasundari, D.R., Kumar, B.S.[B. Santhosh],
Autoregressive-Elephant Herding Optimization based Generative Adversarial Network for copy-move forgery detection with Interval type-2 fuzzy clustering,
SP:IC(108), 2022, pp. 116756.
Elsevier DOI 2209
Copy-move forgery, Image forensics, Generative Adversarial Network (GAN), Elephant Herding Optimization (EHO) BibRef

Yue, G.Y.[Guang-Yu], Duan, Q.[Qing], Liu, R.Y.[Ren-Yang], Peng, W.Y.[Wen-Yu], Liao, Y.[Yun], Liu, J.H.[Jun-Hui],
SMDAF: A novel keypoint based method for copy-move forgery detection,
IET-IPR(16), No. 13, 2022, pp. 3589-3602.
DOI Link 2210
BibRef

Kumar, S.[Sanjeev], Gupta, S.K.[Suneet K.], Kaur, M.[Manjit], Gupta, U.[Umesh],
VI-NET: A hybrid deep convolutional neural network using VGG and inception V3 model for copy-move forgery classification,
JVCIR(89), 2022, pp. 103644.
Elsevier DOI 2212
Copy-move forgery, COMOFOD dataset, Convolution neural network, VGG16, Inception V3 BibRef

Wang, X.Y.[Xiang-Yang], Chen, W.[Wencong], Niu, P.P.[Pan-Pan], Yang, H.Y.[Hong-Ying],
Image copy-move forgery detection based on dynamic threshold with dense points,
JVCIR(89), 2022, pp. 103658.
Elsevier DOI 2212
Copy-move tampering, FJFMs, SLIC, Dynamic threshold, WLD BibRef

Aydin, Y.[Yildiz],
A new Copy-Move forgery detection method using LIOP,
JVCIR(89), 2022, pp. 103661.
Elsevier DOI 2212
Copy-move forgery, LIOP, YCbCr, Keypoint, Image processing BibRef

Shahrokhi, M.[Marziye], Akoushideh, A.[Alireza], Shahbahrami, A.[Asadollah],
Image Copy-Move Forgery Detection Using Combination of Scale-Invariant Feature Transform and Local Binary Pattern Features,
IJIG(22), No. 5 2022, pp. 2250048.
DOI Link 2212
BibRef

Zhang, Y.L.[Yu-Lan], Zhu, G.P.[Guo-Pu], Wang, X.[Xing], Luo, X.Y.[Xiang-Yang], Zhou, Y.C.[Yi-Cong], Zhang, H.L.[Hong-Li], Wu, L.G.[Li-Gang],
CNN-Transformer Based Generative Adversarial Network for Copy-Move Source/ Target Distinguishment,
CirSysVideo(33), No. 5, May 2023, pp. 2019-2032.
IEEE DOI 2305
Feature extraction, Forgery, Convolutional neural networks, Location awareness, Transformers, Generators, transformer BibRef

Rajkumar, R.[Rajeev],
Deep Learning Feature Extraction Using Attention-Based DenseNet 121 for Copy Move Forgery Detection,
IJIG(23), No. 5 2023, pp. 2350042.
DOI Link 2310
BibRef

Duan, H.Y.[Hui-Yu], Shen, W.[Wei], Min, X.K.[Xiong-Kuo], Tian, Y.[Yuan], Jung, J.H.[Jae-Hyun], Yang, X.K.[Xiao-Kang], Zhai, G.T.[Guang-Tao],
Develop Then Rival: A Human Vision-Inspired Framework for Superimposed Image Decomposition,
MultMed(25), 2023, pp. 4267-4281.
IEEE DOI 2310
Separate 2 superimposed images. BibRef

Chen, J.[Jiale], Dong, L.[Li], Wang, R.[Rangding], Yan, D.[Diqun], Peng, C.B.[Cheng-Bin],
Mixed-Bit Sampling Graphic: When Watermarking Meets Copy Detection Pattern,
SPLetters(31), 2024, pp. 286-290.
IEEE DOI 2402
Codes, Watermarking, QR codes, Discrete cosine transforms, Authentication, Graphics, Correlation, Copy detection pattern, image watermarking BibRef

Weng, S.W.[Shao-Wei], Zhu, T.[Tangguo], Zhang, T.C.[Tian-Cong], Zhang, C.Y.[Chun-Yu],
UCM-Net: A U-Net-Like Tampered-Region-Related Framework for Copy-Move Forgery Detection,
MultMed(26), 2024, pp. 750-763.
IEEE DOI 2402
Feature extraction, Finite element analysis, Cross layer design, Semantics, Forgery, Task analysis, Deep learning, ASPP, CMFD, UCM-Net BibRef

Shehin, A.U., Sankar, D.[Deepa],
Copy Move Forgery detection and localisation robust to rotation using block based Discrete Cosine Transform and eigenvalues,
JVCIR(99), 2024, pp. 104075.
Elsevier DOI 2403
Digital image forensics, Copy Move Forgery detection, Anti-forensics, Discrete Cosine Transform, Post-processing, Eigenvalues BibRef

Xiong, L.Z.[Li-Zhi], Xu, J.H.[Jian-Hua], Yang, C.N.[Ching-Nung], Zhang, X.P.[Xin-Peng],
CMCF-Net: An End-to-End Context Multiscale Cross-Fusion Network for Robust Copy-Move Forgery Detection,
MultMed(26), 2024, pp. 6090-6101.
IEEE DOI 2404
Feature extraction, Location awareness, Forgery, Correlation, Software algorithms, Software, Decoding, image forensics BibRef

Hussain, I.[Israr], Tan, S.Q.[Shun-Quan], Huang, J.W.[Ji-Wu],
A knowledge distillation based deep learning framework for cropped images detection in spatial domain,
SP:IC(124), 2024, pp. 117117.
Elsevier DOI 2405
Digital image forensics, Image cropping, Knowledge distillation, Deep learning, Convolutional neural network BibRef

Shi, Y.X.[Yu-Xuan], Weng, S.W.[Shao-Wei], Yu, L.F.[Li-Fang], Li, L.[Li],
Lightweight and High-Precision Network for Image Copy-Move Forgery Detection,
SPLetters(31), 2024, pp. 1409-1413.
IEEE DOI 2405
Feature extraction, Costs, Convolution, Forgery, Spatial resolution, Logic gates, Kernel, Copy-move forgery detection, lightweight, convolutional neural network BibRef

Das, D.[Debjit], Naskar, R.[Ruchira],
Image splicing detection using low-dimensional feature vector of texture features and Haralick features based on Gray Level Co-occurrence Matrix,
SP:IC(125), 2024, pp. 117134.
Elsevier DOI 2405
Classification, Dimensionality reduction, GLCM, Haralick features, Image splicing detection, Localization BibRef

Rathi, K.[Kavita], Singh, P.[Parvinder],
Copy-move forgery detection by improved SIFT K-means algorithm,
IJCVR(14), No. 4, 2024, pp. 339-354.
DOI Link 2407
BibRef


Agrawal, S.[Susmit], Kumar, P.[Prabhat], Seth, S.[Siddharth], Parag, T.[Toufiq], Singh, M.[Maneesh], Babu, V.[Venkatesh],
SISL:Self-Supervised Image Signature Learning for Splicing Detection & Localization,
WMF22(22-32)
IEEE DOI 2210
Training, Location awareness, Social networking (online), Splicing, Forensics, Transforms, Metadata BibRef

Bi, X.L.[Xiu-Li], Zhang, Z.P.[Zhi-Peng], Xiao, B.[Bin],
Reality Transform Adversarial Generators for Image Splicing Forgery Detection and Localization,
ICCV21(14274-14283)
IEEE DOI 2203
Location awareness, Training, Splicing, Transforms, Generative adversarial networks, Forgery, Adversarial learning BibRef

Mahfoudi, G.[Gaël], Morain-Nicolier, F.[Frédéric], Retraint, F.[Florent], Pic, M.[Marc],
CMID: A New Dataset for Copy-Move Forgeries on ID Documents,
ICIP21(3028-3032)
IEEE DOI 2201
Image processing, Companies, Forgery, Detection algorithms, copy-move, dataset, tampering, forgery, document BibRef

Salehi, S.[Saba], Mahmoodi-Aznaveh, A.[Ahmad],
Discriminating the Original Region from the Duplicated in Copy-Move Forgery,
IPRIA21(1-6)
IEEE DOI 2201
Location awareness, Image analysis, Digital images, Visual systems, Benchmark testing, Forgery, Pattern recognition, local binary patterns BibRef

Wu, H.W.[Hai-Wei], Zhou, J.T.[Jian-Tao],
GIID-NET: Generalizable Image Inpainting Detection Network,
ICIP21(3867-3871)
IEEE DOI 2201
Deep learning, Forensics, Image processing, Neural networks, Tools, Forgery, Inpainting forensics, generalizability, deep neural networks BibRef

Kafali, E.[Efthimia], Vretos, N.[Nicholas], Semertzidis, T.[Theodoros], Daras, P.[Petros],
RobusterNet: Improving Copy-Move Forgery Detection with Volterra-based Convolutions,
ICPR21(1160-1165)
IEEE DOI 2105
Location awareness, Image segmentation, Convolution, Feature extraction, Forgery, Robustness, Pattern recognition BibRef

Salman, M.[Muhammad], Uhl, A.[Andreas],
Countering Anti-forensics of SIFT-based Copy-Move Detection,
ICPR21(2701-2707)
IEEE DOI 2105
Cats, Forensics, Games, Forgery, Mice, Pattern recognition BibRef

Zhao, X.Y.[Xiao-Yu], Niu, Y.K.[Ya-Kun], Ni, R.R.[Rong-Rong], Zhao, Y.[Yao],
Defocused Image Splicing Localization by Distinguishing Multiple Cues between Raw Naturally Blur and Artificial Blur,
IWDW20(153-167).
Springer DOI 2103
BibRef

Horváth, J.[János], Montserrat, D.M.[Daniel Mas], Delp, E.J.[Edward J.], Horváth, J.[János],
Nested Attention U-net: A Splicing Detection Method for Satellite Images,
MMForWild20(516-529).
Springer DOI 2103
BibRef

Milosavljevic, N.S.[Nataša S.], Ralevic, N.M.[Nebojša M.],
Fuzzy Metaheuristic Algorithm for Copy-Move Forgery Detection in Image,
IWCIA20(273-281).
Springer DOI 2009
BibRef

Rozsa, A., Boult, T.E., Zhong, Z.,
Adversarial Attack on Deep Learning-Based Splice Localization,
WMF20(2757-2765)
IEEE DOI 2008
Feature extraction, Tools, Cameras, Machine learning, Task analysis, Perturbation methods, Metadata BibRef

Islam, A., Long, C., Basharat, A., Hoogs, A.,
DOA-GAN: Dual-Order Attentive Generative Adversarial Network for Image Copy-Move Forgery Detection and Localization,
CVPR20(4675-4684)
IEEE DOI 2008
Feature extraction, Forgery, Generators, Generative adversarial networks, Task analysis, Kernel, Tools BibRef

Wang, S., Wang, O., Zhang, R., Owens, A., Efros, A.,
Detecting Photoshopped Faces by Scripting Photoshop,
ICCV19(10071-10080)
IEEE DOI 2004
computer graphics, face recognition, image reconstruction, photoshopped faces, malicious photo manipulations, Visualization BibRef

Darmet, L.[Ludovic], Wang, K.[Kai], Cayre, F.[François],
Weakly Supervised Adaptation to Re-sizing for Image Manipulation Detection on Small Patches,
IWDW19(99-114).
Springer DOI 2003
BibRef

Júnior, P.R.M., Bondi, L., Bestagini, P., Rocha, A., Tubaro, S.,
A Prnu-Based Method to Expose Video Device Compositions in Open-Set Setups,
ICIP19(96-100)
IEEE DOI 1910
Video forensics, PRNU, device attribution, open-set BibRef

Mazumdar, A., Bora, P.K.,
Deep Learning-Based Classification of Illumination Maps for Exposing Face Splicing Forgeries in Images,
ICIP19(116-120)
IEEE DOI 1910
Image Forensics, Illumination Inconsistencies, Deep Learning, Siamese Network BibRef

Alyosef, A.A.[Afraŕ Ahmad], Nürnberger, A.[Andreas],
Detecting Sub-Image Replicas: Retrieval and Localization of Zoomed-In Images,
CAIP19(II:257-268).
Springer DOI 1909
BibRef

Bruni, V.[Vittoria], Ramella, G.[Giuliana], Vitulano, D.[Domenico],
An Adaptive Copy-Move Forgery Detection Using Wavelet Coefficients Multiscale Decay,
CAIP19(I:469-480).
Springer DOI 1909
BibRef

Cun, X.D.[Xiao-Dong], Pun, C.M.[Chi-Man],
Image Splicing Localization via Semi-global Network and Fully Connected Conditional Random Fields,
Objectionable18(II:252-266).
Springer DOI 1905
BibRef

Liu, B.[Bo], Pun, C.M.[Chi-Man],
Deep Fusion Network for Splicing Forgery Localization,
Objectionable18(II:237-251).
Springer DOI 1905
BibRef

Dadkhah, S.[Sajjad], Koppen, M., Sadeghi, S.[Somayeh], Yoshida, K., Jalab, H.A., Manaf, A.A.[Azizah Abd],
An efficient ward-based copy-move forgery detection method for digital image forensic,
IVCNZ17(1-6)
IEEE DOI 1902
data compression, feature extraction, image coding, image forensics, image matching, pattern clustering, Digital Image Forensics BibRef

Niyishaka, P.[Patrick], Bhagvati, C.[Chakravarthy],
Digital Image Forensics Technique for Copy-Move Forgery Detection Using DoG and ORB,
ICCVG18(472-483).
Springer DOI 1810
BibRef

Pomari, T., Ruppert, G., Rezende, E., Rocha, A., Carvalho, T.,
Image Splicing Detection Through Illumination Inconsistencies and Deep Learning,
ICIP18(3788-3792)
IEEE DOI 1809
Splicing, Feature extraction, Forgery, Lighting, Task analysis, Training, Forensics BibRef

Wu, Y.[Yue], Abd-Almageed, W.[Wael], Natarajan, P.[Prem],
BusterNet: Detecting Copy-Move Image Forgery with Source/Target Localization,
ECCV18(VI: 170-186).
Springer DOI 1810
BibRef
Earlier:
Image Copy-Move Forgery Detection via an End-to-End Deep Neural Network,
WACV18(1907-1915)
IEEE DOI 1806
affine transforms, convolution, feature extraction, feedforward neural nets, image forensics, Training data BibRef

Novozámsky, A., Šorel, M.,
JPEG compression model in copy-move forgery detection,
IPTA17(1-6)
IEEE DOI 1804
data compression, image coding, image forensics, image texture, JPEG compression model, JPEG-based constraint, Quantization constraint set BibRef

Roy, A., Konda, A., Chakraborty, R.S.,
Copy move forgery detection with similar but genuine objects,
ICIP17(4083-4087)
IEEE DOI 1803
Databases, Estimation, Feature extraction, Forgery, Lighting, Robustness, Transforms, Copy-move forgery, similar but genuine objects BibRef

Khayeat, A.R.H.[Ali Retha Hasoon], Rosin, P.L.[Paul L.], Sun, X.F.[Xian-Fang],
Copy-Move Forgery Detection Using the Segment Gradient Orientation Histogram,
SCIA17(I: 209-220).
Springer DOI 1706
BibRef
Earlier: A1, A3, A2:
Improved DSIFT Descriptor Based Copy-Rotate-Move Forgery Detection,
PSIVT15(642-655).
Springer DOI 1602
BibRef

Kuznetsov, A.[Andrey],
Remote Sensing Data Copy-Move Forgery Protection Algorithm,
ICCVG16(544-552).
Springer DOI 1611
BibRef

Kuznetsov, A.[Andrey], Myasnikov, V.[Vladislav],
A Copy-Move Detection Algorithm Using Binary Gradient Contours,
ICIAR16(349-357).
Springer DOI 1608
BibRef

Kushol, R., Salekin, M.S., Kabir, M.H., Khan, A.A.,
Copy-Move Forgery Detection Using Color Space and Moment Invariants-Based Features,
DICTA16(1-6)
IEEE DOI 1701
Digital images BibRef

Wen, B., Zhu, Y., Subramanian, R., Ng, T.T., Shen, X., Winkler, S.,
COVERAGE: A novel database for copy-move forgery detection,
ICIP16(161-165)
IEEE DOI 1610
Adaptation models BibRef

Cozzolino, D.[Davide], Poggi, G.[Giovanni], Verdoliva, L.[Luisa],
Copy-move forgery detection based on PatchMatch,
ICIP14(5312-5316)
IEEE DOI 1502
Boolean functions BibRef

Al-Qershi, O.M.[Osamah M.], Khoo, B.E.[Bee Ee],
Enhanced Matching Method for Copy-Move Forgery Detection by Means of Zernike Moments,
IWDW14(485-497).
Springer DOI 1602
BibRef

Zhou, L.N.[Lin-Na], Guo, Y.B.[Yun-Biao], You, X.G.[Xin-Gang],
Blind Copy-Paste Detection Using Improved SIFT Ring Descriptor,
IWDW11(257-267).
Springer DOI 1208
BibRef

Murali, S., Anami, B.S., Chittapur, G.B.,
Detection of Copy-Create Image Forgery Using Luminance Level Techniques,
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IEEE DOI 1205
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Muhammad, N.[Najah], Hussain, M.[Muhammad], Muhamad, G.[Ghulam], Bebis, G.N.[George N.],
A Non-intrusive Method for Copy-Move Forgery Detection,
ISVC11(II: 516-525).
Springer DOI 1109
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Li, W.H.[Wei-Hai], Yu, N.H.[Neng-Hai],
Rotation robust detection of copy-move forgery,
ICIP10(2113-2116).
IEEE DOI 1009
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Zhang, T.[Ting], Wang, R.D.[Rang-Ding],
Copy-Move Forgery Detection Based on SVD in Digital Image,
CISP09(1-5).
IEEE DOI 0910
BibRef

Chapter on OCR, Document Analysis and Character Recognition Systems continues in
Source Camera Identification, Camera Fingerprint .


Last update:Jul 13, 2024 at 15:27:21