Results 11 to 20 of about 2,330 (292)
Image forgery detection review
2021 International Conference on Information Systems and Advanced Technologies (ICISAT), 2021 open ...
Benhamza, Hiba +2 more
openaire +3 more sources
A Survey on Photo Forgery Detection Methods
ITM Web of Conferences, 2018 In recent years, digital image forgery detection has become one of the hardest studying area for researchers investigations in the field of information security and image processing.
Gurunlu Bilgehan, Ozturk Serkan
doaj +2 more sources
RIFD-Net: A Robust Image Forgery Detection Network
IEEE AccessImage splicing forensic technologies reveal manipulations that add or remove objects from images. However, the performance of existing splicing forensic methods is fatally degraded when detecting noisy images, as they often ignore the influence of image ...
Wuyang Shan +5 more
doaj +2 more sources
Enhancing Digital Image Forgery Detection Using Transfer Learning
IEEE Access, 2023 Nowadays, digital images are a main source of shared information in social media. Meanwhile, malicious software can forge such images for fake information. So, it’s crucial to identify these forgeries. This problem was tackled in the literature by
Ashgan H. Khalil +4 more
doaj +2 more sources
Image forgery detection via forensic similarity graphs [PDF]
, 2022 In the article 'Exposing Fake Images with Forensic Similarity Graphs', O. Mayer and M. C. Stamm introduce a novel image forgery detection method. The proposed method is built on a graph-based representation of images, where image patches are represented ...
Gardella, Marina, Musé, Pablo
core +1 more source
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
doaj +1 more source
IEEE Access, 2023 Copy-move (CM) forgery is a common type of image manipulation that involves copying and pasting a region within an image to conceal or duplicate content. Detection of such forgeries acts as an important part of digital image forensics.
Mashael Maashi +7 more
doaj +1 more source
Facial depth forgery detection based on image gradient
, 2023 With the widespread application of deep learning, many artificially generated fake images and videos appear on the Internet. However, it is difficult for people to distinguish the real from the fake ones, making the research on detecting and recognizing ...
Fang, Xianjin +7 more
core +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
Demosaicing to Detect Demosaicing and Image Forgeries
2022 IEEE International Workshop on Information Forensics and Security (WIFS), 2022 The truthfulness of images is a critical concern. Digital photographs can no longer be assumed to be truthful; indeed, digital image editing tools can easily and convincingly alter the semantic content of an image. Being able to analyse an image to check for forgeries becomes of the utmost importance in many domains, from police investigations to fact ...
Bammey, Quentin +2 more
openaire +3 more sources