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Detection of copy–move forgery using discrete analytical Fourier–Mellin transform

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Abstract

In recent years, digital image processing has become commonplace with growing powerful and available image editing software. People without any professional technique can also manipulate and forge digital images easily. One of the most popular manners of digital image forgeries is the copy–move image forgery. Extensive researches in detecting copy–move forgery have made a deal of achievements, but most presented methods based on these researches have been only focus on some simple composite forgeries and not able to detect different types of post-processed forgeries. In this paper, we aim to deal with the post-processed forgery operations and scenarios, mainly geometric distortion. We introduce analytical Fourier–Mellin transform (AFMT) and focus on its discretization. We propose discrete analytical Fourier–Mellin transform (DAFMT). We also pay attention to high performance of DAFMT in detecting the copy–move image forgeries. Due to the AFMT described in polar coordinate, so we need to convert coordinate system from polar to Cartesian coordinates. To be computed conveniently, we define an auxiliary disk template to accomplish this conversion. We devote to the use of our proposed DAFMT in detection of image forgeries. A great deal of researches and experiments show that the proposed DAFMT can effectively resist translation, rotation, scaling, and added Gaussian noise operations. Compared with other relevant up-to-date methods, experiments also prove that DAFMT has made a progress in detecting and identifying the forgery images which are suffered from geometric distortion operations.

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Acknowledgments

This work is supported by the 2014 Guangdong Province Young Innovative Talent (Natural Science) Class Project Fund (No. 2014KQNCX256), Guangdong Province College Students’ Science and Technology Innovation Cultivation Project Fund (No. pdjh2015b0642), and Guangdong Mechanical & Electrical College 2015 Technology Plan Projects (Natural Science) Class Project Fund (No. YJKJ2015-1). The authors are grateful for this support.

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Authors and Affiliations

  1. School of Information Engineering, Guangdong Mechanical and Electrical College, Guangzhou, 510550, People’s Republic of China

    Junliu Zhong

  2. Department of Information Science and Technology, Guangdong University of Foreign Studies South China Business College, Guangzhou, 510545, People’s Republic of China

    Yanfen Gan

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  1. Junliu Zhong
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  2. Yanfen Gan
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Correspondence to Yanfen Gan.

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Zhong, J., Gan, Y. Detection of copy–move forgery using discrete analytical Fourier–Mellin transform. Nonlinear Dyn 84, 189–202 (2016). https://doi.org/10.1007/s11071-015-2374-9

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