Results 11 to 20 of about 1,949 (251)

Forgery Detection and Value Identification of Euro Banknotes [PDF]

Sensors, 2013
Sebastiano Battiato, Giovanni Maria Farinella, Giuseppe Claudio Guarnera   +2 more
exaly   +2 more sources

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

Deep Face Forgery Detection

CoRR, 2020
Rapid progress in deep learning is continuously making it easier and cheaper to generate video forgeries. Hence, it becomes very important to have a reliable way of detecting these forgeries. This paper describes such an approach for various tampering scenarios. The problem is modelled as a per-frame binary classification task.
Nika Dogonadze, Jana Obernosterer, Ji Hou   +2 more
openaire   +2 more sources

Face Forgery Detection and Attribution via Prototype Disentanglement [PDF]

Jisuanji kexue yu tansuo
The detection and attribution of face forgery aims to determine whether a face in an image or video has been manipulated or synthesized using Deepfake techniques, as well as to further analyze the Deepfake method behind it.
QIAN Fei, LI Wei, CHEN Peng, CHEN Haoran, XIE Lipeng, LIU Liyuan
doaj   +1 more source

Multi-Feature Fusion Based Deepfake Face Forgery Video Detection

Systems, 2022
With the rapid development of deep learning, generating realistic fake face videos is becoming easier. It is common to make fake news, network pornography, extortion and other related illegal events using deep forgery.
Zhimao Lai, Yufei Wang, Renhai Feng, Xianglei Hu, Haifeng Xu   +4 more
doaj   +1 more source

Seamless Copy–Move Replication in Digital Images

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, Mushtaq Ali, Khizar Hayat, Baptiste Magnier   +3 more
doaj   +1 more source

A Survey On Video Forgery Detection

CoRR, 2015
The Digital Forgeries though not visibly identifiable to human perception it may alter or meddle with underlying natural statistics of digital content. Tampering involves fiddling with video content in order to cause damage or make unauthorized alteration/modification.
Sowmya K. N., H. R. Chennamma
openaire   +2 more sources

Blind Detection of Copy-Move Forgery in Digital Audio Forensics

IEEE Access, 2017
Although copy-move forgery is one of the most common fabrication techniques, blind detection of such tampering in digital audio is mostly unexplored. Unlike active techniques, blind forgery detection is challenging, because it does not embed a watermark ...
Muhammad Imran, Zulfiqar Ali, Sheikh Tahir Bakhsh, Sheeraz Akram   +3 more
doaj   +1 more source

Modeling of Reptile Search Algorithm With Deep Learning Approach for Copy Move Image Forgery Detection

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, Hayam Alamro, Heba Mohsen, Noha Negm, Gouse Pasha Mohammed, Noura Abdelaziz Ahmed, Sara Saadeldeen Ibrahim, Mohamed Ibrahim Alsaid   +7 more
doaj   +1 more source

Copy-Move Forgery Detection and Localization Using a Generative Adversarial Network and Convolutional Neural-Network

Information, 2019
The problem of forged images has become a global phenomenon that is spreading mainly through social media. New technologies have provided both the means and the support for this phenomenon, but they are also enabling a targeted response to overcome it ...
Younis Abdalla, M. Tariq Iqbal, Mohamed Shehata   +2 more
doaj   +1 more source