Results 11 to 20 of about 27,957 (184)
An Evaluation of Popular Copy-Move Forgery Detection Approaches
IEEE Transactions on Information Forensics and Security, 2012 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.
Angelopoulou, Elli +4 more
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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
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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
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Structural Correlation Based Method for Image Forgery Classification and Localization
Applied Sciences, 2020 In the image forgery problems, previous works has been chiefly designed considering only one of two forgery types: copy-move and splicing. In this paper, we propose a scheme to handle both copy-move and splicing image forgery by concurrently classifying ...
Nam Thanh Pham +2 more
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Image Copy-Move Forgery Detection Based on Fused Features and Density Clustering
Applied Sciences, 2023 Image copy-move forgery is a common simple tampering technique. To address issues such as high time complexity in most copy-move forgery detection algorithms and difficulty detecting forgeries in smooth regions, this paper proposes an image copy-move ...
Guiwei Fu, Yujin Zhang, Yongqi Wang
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SMDAF: A novel keypoint based method for copy‐move forgery detection
IET Image Processing, 2022 Copy–move forgery poses a significant threat to social life and has aroused much attention in recent years. Although many copy‐move forgery detection (CMFD) methods have been proposed, the most existing CMFD methods are short of adaptability in detecting
Guangyu Yue +5 more
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An Optimal Hybrid Method to Detect Copy-move Forgery [PDF]
Journal of Artificial Intelligence and Data Mining, 2023 Image is a powerful communication tool that is widely used in various applications, such as forensic medicine and court, where the validity of the image is crucial. However, with the development and availability of image editing tools, image manipulation
Fatemeh Zare mehrjardi +2 more
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Copy Move Forgery Detection with Quadtree Decomposition Segmentation
2020 43rd International Conference on Telecommunications and Signal Processing (TSP), 2020 The increasing usage of digital images and the wide availability of easy-to-use image editors have made the authenticity of images questionable. Copy-move is one of the most applied forgery types. The keypoint-based copy move forgery detection methods in the literature cannot detect forgeries with smooth regions. In this paper to overcome this problem,
Muzaffer, Gul +2 more
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Copy-move forgery detection using the segment gradient orientation histogram [PDF]
, 2017 The ready availability of image-editing software makes ensuring the authenticity of images an important issue. The most common type of image tampering is cloning, or Copy-Move Forgery (CMF), in which part(s) of the image are copied and pasted back into ...
Khayeat, Ali +2 more
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Copy Move Image Forgery Detection Using SIFT [PDF]
Oriental journal of computer science and technology, 2016 In recent years the digital form of data allowing ease on to manipulation & storage due to progress in technology. But this progress in technology has lots of risks especially when it comes to the security of the digital data & files. Basically, image forgery means malfunctioning & playing with images or manipulating data fraudulently.
Priyanka Ruikar, Pravin Patil
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