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A novel robust zero-watermarking algorithm for medical images

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Abstract

A novel robust zero-watermarking algorithm for medical images is presented in this paper. The multi-scale decomposition of bi-dimensional empirical mode decomposition (BEMD) has exhibited many attractive properties that enable the proposed algorithm to robustly detect the tampering regions and protect the copyright of medical images simultaneously. Given a medical image, we first decompose a medical image adaptively into a finite number of intrinsic mode functions (IMFs) and a residue, by taking a full advantage of BEMD. The first IMF starts with the finest scale retaining fragile information and is best suitable for tampering detection, while the residue includes robust information at the coarser scale and is applied to the protection of intellectual property rights of medical images. Next, the feature matrices are extracted from the first IMF and the residue via singular value decomposition, which achieves robust performance subject to most attacks. For a given watermark image, it is encrypted by Arnold transform to enhance the security of the watermark. Then, the feature images are constructed by performing the exclusive-or operation between the encrypted watermark image and the extracted feature matrices. Finally, the feature images are securely stored in the copyright authentication database to be further used for copyright authentication and tampering detection. A large number of experimental results and comparisons with existing watermarking algorithms confirm that the newly proposed watermarking algorithm not only has strong ability on tampering detection, but also has better performance in combating various attacks, including cropping, Gaussian noise, median filtering, image enhancement attacks, etc. The newly developed algorithm also shows great promise in processing natural images.

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Funding

This research is supported in part by National Science Foundation of USA (IIS-1715985 and IIS-1812606), National Natural Science Foundation of China (Nos. 61532002, 61672077, 61672149, 61802279, 61872347); The Science & Technology Development Fund of Tianjin Education Commission for Higher Education (Grant No. 2018 KJ222); The Open Project Program of the State Key Lab of CAD&CG (Grant No. A2105), Zhejiang University.

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Authors and Affiliations

  1. Chinese Academy of Sciences, Beijing, 100049, China

    Kun Hu

  2. School of Mathematical Sciences, Tiangong University, Tianjin, 300387, China

    Xiaochao Wang

  3. School of Sciences, Northeast Electric Power University, Jilin, 132012, China

    Jianping Hu

  4. Key Laboratory of Space Utilization, Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing, 100094, China

    Hongfei Wang

  5. Department of Computer Science, Stony Brook University, Stony Brook, NY, 11794-4400, USA

    Hong Qin

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  1. Kun Hu
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  2. Xiaochao Wang
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  3. Jianping Hu
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  4. Hongfei Wang
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  5. Hong Qin
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Correspondence to Xiaochao Wang or Hongfei Wang.

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Hu, K., Wang, X., Hu, J. et al. A novel robust zero-watermarking algorithm for medical images. Vis Comput 37, 2841–2853 (2021). https://doi.org/10.1007/s00371-021-02168-5

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