SPA-Net: A Deep Learning Approach Enhanced Using a Span-Partial Structure and Attention Mechanism for Image Copy-Move Forgery Detection [PDF]
Sensors, 2023 With the wide application of visual sensors and development of digital image processing technology, image copy-move forgery detection (CMFD) has become more and more prevalent.
Kaiqi Zhao +5 more
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Unveiling Copy-Move Forgeries: Enhancing Detection With SuperPoint Keypoint Architecture
IEEE Access, 2023 The authentication of digital images poses a significant challenge due to the wide range of image forgery techniques employed, with one notable example being a copy-move forgery.
Anjali Diwan +4 more
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Frequency domain manipulation of multiple copy-move forgery in digital image forensics. [PDF]
PLoS ONECopy move forgery is a type of image forgery in which a portion of the original image is copied and pasted in a new location on the same image. The consistent illumination and noise pattern make this kind of forgery more difficult to detect. In copy-move
Tanzeela Qazi +5 more
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Image copy-move forgery detection and localization based on super-BPD segmentation and DCNN [PDF]
Scientific Reports, 2022 With the increasing importance of image information, image forgery seriously threatens the security of image content. Copy-move forgery detection (CMFD) is a greater challenge because its abnormality is smaller than other forgeries.
Qianwen Li +3 more
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LBRT: Local-Information-Refined Transformer for Image Copy–Move Forgery Detection [PDF]
SensorsThe current deep learning methods for copy–move forgery detection (CMFD) are mostly based on deep convolutional neural networks, which frequently discard a large amount of detail information throughout convolutional feature extraction and have poor long ...
Peng Liang +3 more
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Seamless Copy–Move Replication in Digital Images [PDF]
Journal of Imaging, 2022 The importance and relevance of digital-image forensics has attracted researchers to establish different techniques for creating and detecting forgeries.
Tanzeela Qazi +3 more
doaj +2 more sources
CFDMI-SEC: An optimal model for copy-move forgery detection of medical image using SIFT, EOM and CHM. [PDF]
PLoS ONEImage forgery is one of the issues that can create challenges for law enforcement. Digital devices can easily Copy-move images, forging medical photos. In the insurance industry, forensics, and sports, image forgery has become very common and has created
Ehsan Amiri +2 more
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CNN-Keypoint Based Two-Stage Hybrid Approach for Copy-Move Forgery Detection
IEEE AccessAuthenticating digital images poses a significant challenge due to the widespread use of image forgery techniques, including copy-move forgery. Copy-move forgery involves copying and pasting portions of an image within the same image while applying ...
Dr. Anjali Diwan, Anil Kumar Roy
exaly +3 more sources
Method for Image Forgery Detection Based on Deformable Self-Correlation Network [PDF]
Jisuanji gongcheng, 2021 The deep learning-based copy-move forgery detection methods ignore the spatial layout of the features, leading to a reduction in the detection performance for small-region forgery samples.Additionally,the fixed size of the receptive fields in ...
LIANG Peng, WU Yuting, ZHAO Huimin, LI Chunying, HE Wa, LI Shaofa
doaj +1 more source
An Efficient CNN Model to Detect Copy-Move Image Forgery
IEEE Access, 2022 Recently, digital images have become used in many applications, where they have become the focus of digital image processing researchers. Image forgery represents one hot topic on which researchers prioritize their studies.
Khalid M. Hosny +3 more
doaj +1 more source