Results 81 to 90 of about 13,696 (179)

ECMNet: A deep framework for copy move forgery localization detection and classification

Results in Engineering
Copy-move forgery is one of the most prevalent forms of digital image forgery. It violates the authenticity of digital images in the context of documentation, judicial reports, social media, military operations, journalism, intelligence, and so on ...
Anjani Kumar Rai, Subodh Srivastava
doaj   +1 more source

Copy Move Image Forgery Detection using Multi-Level Local Binary Pattern Algorithm

Journal of Engineering
Digital image manipulation has become increasingly prevalent due to the widespread availability of sophisticated image editing tools. In copy-move forgery, a portion of an image is copied and pasted into another area within the same image.
Marwa Emad Mahdi, Nada Hussein M Ali
doaj   +1 more source

The PS-Battles Dataset - an Image Collection for Image Manipulation Detection

, 2018
The boost of available digital media has led to a significant increase in derivative work. With tools for manipulating objects becoming more and more mature, it can be very difficult to determine whether one piece of media was derived from another one or
Heller, Silvan, Rossetto, Luca, Schuldt, Heiko   +2 more
core  

Image Forgery and Detection of Copy Move Forgery in Digital Images: A Survey of Recent Forgery Detection Techniques

International Journal of Computer Applications, 2016
With the development of Image processing editing tools and software, an image is manipulated very easily. The image manipulation detection is essential for the reason that an image can be employed as legal evidence, in the field of forensics investigations, and also in numerous various other fields.
openaire   +1 more source

Image Forgery Detection and Localization via a Reliability Fusion Map. [PDF]

Sensors (Basel), 2020
Yao H, Xu M, Qiao T, Wu Y, Zheng N.
europepmc   +1 more source

An Enhanced Hybrid Method based on Local and Frequency Feature Extraction for Image Copy Move Forgery Detection

Majlesi Journal of Electrical Engineering
Today, due to the advent of the powerful photo editing software packages, it has become relatively easy to create forgery images. Recognizing the correctness of digital images becomes important when those images are used as evidence in legal, forensic ...
Shirin Nayerdinzadeh, Mohammad Yousefi
doaj   +1 more source

BMNet: Enhancing Deepfake Detection Through BiLSTM and Multi-Head Self-Attention Mechanism

IEEE Access
When forgery techniques can generate highly realistic videos, traditional convolutional neural network (CNN)-based detection models often struggle to capture subtle forgery features and temporal dependencies.
Demao Xiong, Zhan Wen, Cheng Zhang, Dehao Ren, Wenzao Li   +4 more
doaj   +1 more source

Design of Automated Deep Learning-Based Fusion Model for Copy-Move Image Forgery Detection.

Comput Intell Neurosci, 2022
Krishnaraj N, Sivakumar B, Kuppusamy R, Teekaraman Y, Thelkar AR, Thelkar AR.   +5 more
europepmc   +1 more source

Detection of Image Forgery [PDF]

International Journal of Engineering Research and, 2020
openaire   +1 more source

Analysis of Copy-move Manipulation in Digital Images using Scale Invariant Feature Transform (SIFT) and SVD-matching Methods

Journal of Applied Informatics and Computing
In recent years, more and more data has been created in digital form, allowing for easier control over storage and manipulation thanks to technological advancements.
Muhamad Masjun Efendi, Nukman Nukman
doaj   +1 more source