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2021 | OriginalPaper | Chapter

Copy-Move Forgery Detection Methods: A Critique

Authors : Monika Kharanghar, Amit Doegar

Published in: Advances in Information Communication Technology and Computing

Publisher: Springer Singapore

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Abstract

With the advancement of image editing tools, legitimacy and creditability of the images are put in jeopardy. There are various types of image forgeries techniques like splicing, retouching, false captioning, and copy-move. But the most predominant forgery techniques are splicing and copy-move forgery. In copy-move forgery, a part of the image is copied in the same image and in splicing another image in order to conceal or to duplicate the information residing in the image. In this critique, the copy-move forgery detection (CMFD) methods from 2013 onwards are reviewed under four categories—block-based, keypoint-based, hybrid-, and deep learning-based methods.

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Metadata
Title
Copy-Move Forgery Detection Methods: A Critique
Authors
Monika Kharanghar
Amit Doegar
Copyright Year
2021
Publisher
Springer Singapore
Book
Advances in Information Communication Technology and Computing

Print ISBN: 978-981-15-5420-9

Electronic ISBN: 978-981-15-5421-6

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-981-15-5421-6_49