Forgery Detection in Digital Images

Authored by: Zhou Zhili , Cao Yi , Sun Xingming , Yang Ching-Nung

Encyclopedia of Image Processing

Print publication date:  November  2018
Online publication date:  November  2018

Print ISBN: 9781482244908
eBook ISBN: 9781351032742
Adobe ISBN:

10.1201/9781351032742-140000122

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Abstract

With the increasing popularity of digital image and the wide use of image processing tools, a large number of digital images are replicated, transmitted, and redistributed via networks. The problem of copy forgeries has become more and more serious in various fields like entertainment, digital forensics, and journalism. Also, people become increasingly aware of their rights under copyright laws. Thus, the copyright protection of digital image is necessarily required. To prevent the illegal use of copyrighted images (original images), image copy forgery detection is developed to detect image copies, which are derived from an original image via various copy attacks such as geometric transformation and noise-like contamination. In the past two decades, a large number of image copy detection methods had been proposed. Those detection methods were categorized into four types: global feature-based detection, local feature-based detection, feature combination-based detection and learning feature-based detection. In this work, we review the key technologies of those detection methods, and meanwhile discuss their advantages and disadvantages, respectively. Furthermore, we also give related challenges and possible solutions.

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