A Comparison Study on Copy-Cover Image Forgery Detection



Frank Y. Shih*, Yuan Yuan
Department of Computer Science, New Jersey Institute of Technology, Newark, NJ 07102, USA


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© 2017 Shih et al.;

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the Department of Computer Science, New Jersey Institute of Technology, Newark, NJ 07102, USA; Tel: 973-596-5654; Fax: 973-596-5777; E-mail:frank.y.shih@njit.edu


Abstract

Due to rapid advances and availabilities of powerful image processing software, digital images are easy to manipulate and modify for ordinary people. This makes it more and more difficult for a viewer to check the authenticity of a given digital image. For digital photographs to be used as evidence in law issues or to be circulated in mass media, it is inevitably needed to identify whether an image is authentic or not. In this paper, we discuss the techniques of copy-cover image forgery and compare four detection methods for copy-cover forgery detection, which are based on PCA, DCT, spatial domain, and statistical domain. We investigate their effectiveness and sensitivity under the influences of Gaussian blurring and lossy JPEG compressions. It is concluded that the PCA method outperforms the others in terms of time complexity and accuracy. In JPEG compression simulation, its true positive rate is above 90% and false positive rate is above 99%. In Gaussian blurring simulation, its true positive rate is above 77% and false positive rate is above 99%.

Keywords: Digital forensics, copy-cover detection, image forgery, image splicing.