Results 41 to 50 of about 13,849 (178)

Optimization of a Pre-Trained AlexNet Model for Detecting and Localizing Image Forgeries

Information, 2020
With the advance of many image manipulation tools, carrying out image forgery and concealing the forgery is becoming easier. In this paper, the convolution neural network (CNN) innovation for image forgery detection and localization is discussed. A novel
Soad Samir, Eid Emary, Khaled El-Sayed, Hoda Onsi   +3 more
doaj   +1 more source

CoMoFoD #x2014; New database for copy-move forgery detection [PDF]

, 2013
Due to the availability of many sophisticated image processing tools, a digital image forgery is nowadays very often used. One of the common forgery method is a copy-move forgery, where part of an image is copied to another location in the same image ...
Grgic, M, Grgic, S, Tralic, D, Zupancic, I   +3 more
core  

Recasting Residual-based Local Descriptors as Convolutional Neural Networks: an Application to Image Forgery Detection

, 2017
Local descriptors based on the image noise residual have proven extremely effective for a number of forensic applications, like forgery detection and localization.
Cozzolino, Davide, Poggi, Giovanni, Verdoliva, Luisa   +2 more
core   +1 more source

Multiple Image Splicing Dataset (MISD): A Dataset for Multiple Splicing

Data, 2021
Image forgery has grown in popularity due to easy access to abundant image editing software. These forged images are so devious that it is impossible to predict with the naked eye. Such images are used to spread misleading information in society with the
Kalyani Dhananjay Kadam, Swati Ahirrao, Ketan Kotecha   +2 more
doaj   +1 more source

Review on passive approaches for detecting image tampering [PDF]

, 2014
This paper defines the presently used methods and approaches in the domain of digital image forgery detection. A survey of a recent study is explored including an examination of the current techniques and passive approaches in detecting image tampering ...
Hashem, Fatma Salman, Sulong, Ghazali
core  

Hybrid LSTM and Encoder-Decoder Architecture for Detection of Image Forgeries

, 2019
With advanced image journaling tools, one can easily alter the semantic meaning of an image by exploiting certain manipulation techniques such as copy-clone, object splicing, and removal, which mislead the viewers.
Bappy, Jawadul H., Manjunath, B. S., Nataraj, Lakshmanan, Roy-Chowdhury, Amit K., Simons, Cody   +4 more
core   +1 more source

A PatchMatch-based Dense-field Algorithm for Video Copy-Move Detection and Localization

, 2017
We propose a new algorithm for the reliable detection and localization of video copy-move forgeries. Discovering well crafted video copy-moves may be very difficult, especially when some uniform background is copied to occlude foreground objects.
Huang, Dawei, Li, Zi, Liu, Yang, Noort, Simon Van, Rasplus, Jean-Yves   +4 more
core   +1 more source

Robust forgery detection for compressed images using CNN supervision

Forensic Science International: Reports, 2020
Images available on online sharing platforms have a high probability of being modified, with additional global transformations such as compression, resizing or filtering covering the possible alteration.
Boubacar Diallo, Thierry Urruty, Pascal Bourdon, Christine Fernandez-Maloigne   +3 more
doaj   +1 more source

Image Forgery Localization Based on Multi-Scale Convolutional Neural Networks

, 2018
In this paper, we propose to utilize Convolutional Neural Networks (CNNs) and the segmentation-based multi-scale analysis to locate tampered areas in digital images.
Cao, Yun, Guan, Qingxiao, Liu, Yaqi, Zhao, Xianfeng   +3 more
core   +1 more source

Autoencoder with recurrent neural networks for video forgery detection

, 2017
Video forgery detection is becoming an important issue in recent years, because modern editing software provide powerful and easy-to-use tools to manipulate videos.
Cozzolino, Davide, D'Avino, Dario, Poggi, Giovanni, Verdoliva, Luisa   +3 more
core   +1 more source