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Multi-scale feature extraction and adaptive matching for copy-move forgery detection

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Abstract

A copy-move forgery detection scheme by using multi-scale feature extraction and adaptive matching is proposed in this paper. First, the host image is segmented into the non-overlapping patches of irregular shape in different scales. Then, Scale Invariant Feature Transform is applied to extract feature points from all patches, to generate the multi-scale features. An Adaptive Patch Matching algorithm is subsequently proposed for finding the matching that indicate the suspicious forged regions in each scale. Finally, the suspicious regions in all scales are merged to generate the detected forgery regions in the proposed Matched Keypoints Merging algorithm. Experimental results show that the proposed scheme performs much better than the existing state-of-the-art copy-move forgery detection algorithms, even under various challenging conditions, including the geometric transforms, such as scaling and rotation, and the common signal processing, such as JPEG compression and noise addition; in addition, the special cases such as the multiple copies and the down-sampling are also evaluated, the results indicate the very good performance of the proposed scheme.

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Acknowledgement

This research was supported in part by the Research Committee of the University of Macau (MYRG2015-00011-FST, MYRG2015-00012-FST) and the Science and Technology Development Fund of Macau SAR (008/2013/A1, 093-2014-A2).

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Authors and Affiliations

  1. Department of Computer and Information Science, University of Macau, Macau, China

    XiuLi Bi & Chi-Man Pun

  2. Faculty of Information Technology, Macau University of Science and Technology, Macau, China

    Xiao-Chen Yuan

Authors
  1. XiuLi Bi
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  2. Chi-Man Pun
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  3. Xiao-Chen Yuan
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Correspondence to Chi-Man Pun.

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Bi, X., Pun, CM. & Yuan, XC. Multi-scale feature extraction and adaptive matching for copy-move forgery detection. Multimed Tools Appl 77, 363–385 (2018). https://doi.org/10.1007/s11042-016-4276-3

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  • DOI: https://doi.org/10.1007/s11042-016-4276-3

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