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Robustness of copy-move forgery detection under high JPEG compression artifacts

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Abstract

This paper proposes a robust method for detecting copy-move forgery in images under various JPEG compression and Gaussian noise and blurring attacks. The method comprises feature extraction, feature matching, and duplicate block identification. The fast Fourier transform (FFT), singular value decomposition (SVD), and principal component analysis (PCA) are utilized for feature extraction. Then, the cascading matchers of FFT, SVD, and PCA are adopted for feature matching. Matched blocks are identified using cascade filtering with city block, horizontal, vertical, and frequency filters. Finally, the pixels on upper left corners of detected duplicate blocks are output for visual inspection. The major contributions of this paper are: (1) the proposed method is fully threshold-free; (2) only one-dimensional features are generated using FFT and SVD for feature matching; and (3) a high accuracy rate (> 97 %) is obtained even if the JPEG quality factor Q is 20. In extensive experiments, a 98 % accuracy rate and a 6 % false negative rate were obtained for the worst case of Q = 20 and a region size of 32 × 32 pixels compared to existing works, indicating the feasibility of the proposed method.

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Acknowledgments

This paper was in part financially supported by the Ministry of Science and Technology, Taiwan, under grants NSC 102-2221-E-212-015, MOST 104-2221-E-212-005, and MOST 104-2218-E-212-001.

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Authors and Affiliations

  1. Department of Electrical Engineering, Da-Yeh University, 168 University Road, Dacun, Changhua, Taiwan

    Deng-Yuan Huang, Ching-Ning Huang & Chih-Hung Chou

  2. Department of Computer Science and Information Engineering, National Penghu University of Science and Technology, 300 Liu-Ho Road, Makung City, Penghu, Taiwan

    Wu-Chih Hu

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  1. Deng-Yuan Huang
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  2. Ching-Ning Huang
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  3. Wu-Chih Hu
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  4. Chih-Hung Chou
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Correspondence to Deng-Yuan Huang.

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Huang, DY., Huang, CN., Hu, WC. et al. Robustness of copy-move forgery detection under high JPEG compression artifacts. Multimed Tools Appl 76, 1509–1530 (2017). https://doi.org/10.1007/s11042-015-3152-x

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  • DOI: https://doi.org/10.1007/s11042-015-3152-x

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