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Copy-move forgery detection based on multifractals

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Abstract

Digital images and video are the basic media for communication nowadays. They are used as authenticated proofs or corroboratory evidence in different areas like: forensic studies, law enforcement, journalism and others. With development of software for editing digital images, it has become very easy to change image content, add or remove important information or even to make one image combining multiple images. Thus, the development of methods for such change detection has become very important. One of the most common methods is copy-move forgery detection (CMFD). Methods of this type include change detection that occur by copying a part of an image and pasting it to another location within the image. We propose new method for detection of such changes using certain multifractal parameters as characteristic features, as well as common statistical parameters. Before the analysis, images are divided into non-overlapping blocks of fixed dimensions. For each block, the characteristic features are calculated. In order to classify observed blocks, we used metaheuristic method and proposed new semi-metric function for similarity analysis between blocks. Simulation shows that the proposed method provides good results in terms of precision and recall, with low computational complexity.

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Acknowledgements

This work has been supported by the Serbian Ministry of Science, Grant nos. III044006, III44009 and TR32023.

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Authors and Affiliations

  1. Telecommunications Department, School of Electrical Engineering, University of Belgrade, Bulevar kralja Aleksandra 73, Belgrade, 11020, Serbia

    Aleksandra Pavlović, Ana Gavrovska & Irini Reljin

  2. Department of Technical Sciences, State University of Novi Pazar, Vuka Karadzica, Novi Pazar, 36300, Serbia

    Aleksandra Pavlović & Natasa Glišović

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  1. Aleksandra Pavlović
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  2. Natasa Glišović
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  3. Ana Gavrovska
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  4. Irini Reljin
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Correspondence to Aleksandra Pavlović.

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Pavlović, A., Glišović, N., Gavrovska, A. et al. Copy-move forgery detection based on multifractals. Multimed Tools Appl 78, 20655–20678 (2019). https://doi.org/10.1007/s11042-019-7277-1

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