Results 31 to 40 of about 79,494 (188)

Image Copy-Move Forgery Detection Based on Fused Features and Density Clustering

open access: yesApplied 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

Combining cellular automata and local binary patterns for copy-move forgery detection [PDF]

open access: yes, 2016
Detection of duplicated regions in digital images has been a highly investigated field in recent years since the editing of digital images has been notably simplified by the development of advanced image processing tools.
Faculty of Electrical Engineering and Computing, University of Zagreb   +5 more
core   +1 more source

ResTran: Long Distance Relationship on Image Forgery Detection

open access: yesIEEE Access, 2023
Image tampering detection is becoming more and more important in image forensics, especially in today’s society where advanced image editing tools are becoming more and more popular.
Jingjing Rao   +2 more
doaj   +1 more source

Blind Detection of Copy-Move Forgery in Digital Audio Forensics

open access: yesIEEE 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   +3 more
doaj   +1 more source

Detection of Geometric Transformations in Copy-Move Forgery of Digital Images [PDF]

open access: yes, 2015
Digital Forensics is a branch of forensic science which is related to cyber crime. It basically involves the detection, recovery and investigation of material found in digital devices.
Shandilya, Meenal
core   +1 more source

Cascaded Two-Stream Attention Networks for Traceability Analysis of Copy-Move Images [PDF]

open access: yesJisuanji kexue yu tansuo, 2023
Copy-move is a common way of the image forgery. Traditional methods are committed to locating tam-pering regions of copy-move tampering images, but the accurate distinction between the source and target of the copy-move image has become a bottleneck in ...
JI Yanqing, ZHANG Yujin
doaj   +1 more source

Recognition of animated icons by elementary‐aged children [PDF]

open access: yes, 1993
This paper describes a study to investigate the recognizability of and preference for animated icons by elementary‐aged aged children. Fourteen typical computer‐related tasks (e.g., copy, move) were viewed by 60 school‐children in two iconic formats ...
Jones, Tom
core   +3 more sources

Copy-Move Image Forgery Detection a Review [PDF]

open access: yesInternational Journal of Image, Graphics and Signal Processing, 2016
Due to the availability of various image processing tools forgery over an image can be performed very easily but very difficult to identify. In copy-move forgery, a segment is copied from the original image and pasted at some other location on the same image to hide significant objects of image or to bring additional information which is originally not
Anuja Dixit, R. K. Gupta
openaire   +1 more source

Fusion of block and keypoints based approaches for effective copy-move image forgery detection [PDF]

open access: yes, 2016
Keypoint-based and block-based methods are two main categories of techniques for detecting copy-move forged images, one of the most common digital image forgery schemes. In general, block-based methods suffer from high computational cost due to the large
Liu, Yanan   +5 more
core   +1 more source

Nonoverlapping Blocks Based Copy-Move Forgery Detection

open access: yesSecurity and Communication Networks, 2018
In order to solve the problem of high computational complexity in block-based methods for copy-move forgery detection, we divide image into texture part and smooth part to deal with them separately. Keypoints are extracted and matched in texture regions.
Yu Sun, Rongrong Ni, Yao Zhao
openaire   +1 more source

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