Results 51 to 60 of about 13,696 (179)

False Matches Removing in Copy-Move Forgery Detection Algorithms

Al-Mustansiriyah Journal of Science, 2020
Today the technology age is characterized by spreading of digital images. The most common form of transfer the information in magazines, newspapers, scientific journals and all types of social media.
muthana salih mahdi, Saad N. Alsaad
doaj   +1 more source

An Improved Statistic for the Pooled Triangle Test against PRNU-Copy Attack

, 2018
We propose a new statistic to improve the pooled version of the triangle test used to combat the fingerprint-copy counter-forensic attack against PRNU-based camera identification [1].
Barni, Mauro, Garcia, Hector Santoyo, Tondi, Benedetta   +2 more
core   +1 more source

Review on tools for image detection forgery [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  

Image Splicing Localization Using A Multi-Task Fully Convolutional Network (MFCN)

, 2017
In this work, we propose a technique that utilizes a fully convolutional network (FCN) to localize image splicing attacks. We first evaluated a single-task FCN (SFCN) trained only on the surface label.
Kuo, C. -C. Jay, Ren, Yuzhuo, Salloum, Ronald   +2 more
core   +1 more source

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

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

Handwritten Signature Verification using Deep Learning [PDF]

, 2020
Every person has his/her own unique signature that is used mainly for the purposes of personal identification and verification of important documents or legal transactions.
Abu-Naser, Samy S., Abu-Nasser, Bassem S., Alajrami, Eman, Ashqar, Belal A. M., Barhoom, Alaa M., Khalil, Ahmed J., Musleh, Musleh M.   +6 more
core  

RST Invariant Image Forgery Detection

Indian Journal of Science and Technology, 2016
Background/Objectives: Copy-Move Forgery Detection (CMFD) is a very prevalent approach used to detect copy and pasted portions of the same image. The copied portion is rotated, flipped or scaled. The detection method should be invariant to rotation, scaling and translation. Many CMFD methods came into existence; however, some methods fail to withstand
Gulivindala Suresh, Chanamallu Srinivasa Rao   +1 more
openaire   +1 more source

Detection of Copy-Move Forgery in Digital Images Using Scale Invariant Feature Transform Algorithm and the Spearman Relationship

Iranian Journal of Electrical and Electronic Engineering, 2020
Increased popularity of digital media and image editing software has led to the spread of multimedia content forgery for various purposes. Undoubtedly, law and forensic medicine experts require trustworthy and non-forged images to enforce rights.
A. Fattahi, S. Emadi
doaj  

Digital Image Forgery Detection

International Journal of Recent Technology and Engineering, 2019
With the growing challenges in authenticity and integrity of images, image manipulation has crumbled assurance over digital image. The major motivation of the forgery in image is manipulating the image in such a way that it cannot be distinguished to the naked eye.
openaire   +1 more source