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Keypoint-based copy-move detection scheme by adopting MSCRs and improved feature matching

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Abstract

Copy-move detection is to find the existence of duplicated regions in an image. In this paper, an effective method based on region features is proposed to detect copy-move forgeries, especially when the image is multiple copied or with multiple copy-move groups. Firstly, maximally stable color region detector is applied to extract features, and these features are represented by Zernike moments. Then an improved matching strategy considering n best-matching features is applied to deal with the multiple-copied problem. Moreover, a hierarchical cluster algorithm is developed to estimate transformation matrices and confirm the existence of forgery. Based on these matrices, the duplicated regions can be located at pixel level. Experimental results indicate that the proposed scheme outperforms other similar state-of-the-art techniques.

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Authors and Affiliations

  1. School of Data and Computer Science, Guangdong Key Laboratory of Information Security Technology, Sun Yat-sen University, Guangzhou, 510006, China

    Jingwei Li & Wei Lu

  2. School of Electronics and Information Engineering, Key Laboratory of Information Technology (Ministry of Education), Sun Yat-sen University, Guangzhou, 510006, China

    Fan Yang & Wei Sun

Authors
  1. Jingwei Li
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  2. Fan Yang
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  3. Wei Lu
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  4. Wei Sun
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Corresponding author

Correspondence to Wei Lu.

Additional information

This work is supported by the Natural Science Foundation of Guangdong (No. 2016A030313350), the Special Funds for Science and Technology Development of Guangdong (No. 2016KZ010103), the Fundamental Research Funds for the Central Universities (No. 16LGJC83). This work is supported in part by the National Natural Science Foundation of China (Nos. U1536203 and 61272409).

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Li, J., Yang, F., Lu, W. et al. Keypoint-based copy-move detection scheme by adopting MSCRs and improved feature matching. Multimed Tools Appl 76, 20483–20497 (2017). https://doi.org/10.1007/s11042-016-3967-0

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  • DOI: https://doi.org/10.1007/s11042-016-3967-0

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