An efficient copy move forgery detection using deep learning feature extraction and matching algorithm

The image forgery activities are on the rise because of the development of various image editing tools. Such activities are done by attackers with intentions of defaming people and websites or for gaining monetary advantage, extortion etc. Image forgeries are carried out through various ways, among...

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Veröffentlicht in:	Multimedia tools and applications Jg. 79; H. 11-12; S. 7355 - 7376
Hauptverfasser:	Agarwal, Ritu, Verma, Om Prakash
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.03.2020 Springer Nature B.V
Schlagworte:	Algorithms Computer Communication Networks Computer Science Computing time Copying Data Structures and Information Theory Deep learning Feature extraction Forgery Image contrast Image detection Image segmentation Machine learning Multimedia Information Systems Special Purpose and Application-Based Systems Websites Copy-move detection Tampered image identification Digital image forgery
ISSN:	1380-7501, 1573-7721
Online-Zugang:	Volltext
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