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Fast and robust copy-move forgery detection based on scale-space representation

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Abstract

Copy-move forgery (CMF), which copies a part of an image and pastes it into another region, is one of the most common methods for digital image tampering. For CMF detection (CMFD), we propose a fast and robust approach that can handle several geometric transformations including rotation, scaling, sheering, and reflection. In the proposed CMFD design, keypoints and their descriptors are extracted from the image based on the Scale Invariant Feature Transform (SIFT). Then, an improved matching operation that can handle multiple copy-move forgeries is performed to detect matched pairs located in duplicated regions. Next, the geometric transformation between duplicated regions is estimated using a subset of reliable matched pairs which are obtained using the SIFT scale space representation. In our simulation, we present comparative results between the proposed algorithm and state-of-the-art ones with proven performance guarantees.

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Acknowledgements

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (NRF-2016R1C1B1009682). This research was supported by the MSIT(Ministry of Science and ICT), Korea, under the ITRC(Information Technology Research Center) support program(IITP-2017-2016-0-00312) supervised by the IITP(Institute for Information & communications Technology Promotion).

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Authors and Affiliations

  1. Department of Computer Education, Sungkyunkwan University, Seoul, South Korea

    Chun-Su Park

  2. Department of Software, Sejong University, Seoul, South Korea

    Joon Yeon Choeh

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  1. Chun-Su Park

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  2. Joon Yeon Choeh

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Correspondence toJoon Yeon Choeh.

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Park, CS., Choeh, J. Fast and robust copy-move forgery detection based on scale-space representation.Multimed Tools Appl77, 16795–16811 (2018). https://doi.org/10.1007/s11042-017-5248-y

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