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Modified Zernike Moments and Its Application in Geometrically Resilient Image Zero-Watermarking

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Abstract

Traditional watermarking, which embeds watermark information into images for copyright protection, cannot be effectively used in applications with high integrity requirements such as medical and military images, because watermark embedding will destroy original images. We propose a robust modified Zernike moments (MZMs)-based zero-watermarking algorithm for image copyright protection without changing the original image. In this paper, a new type of radial basis function of Zernike moments (ZMs) is designed, and based on this, MZMs are constructed, which effectively improves the performance of ZMs. Then a robust geometric-attack-resistant zero-watermarking algorithm based on MZMs is proposed for image lossless copyright protection. Experimental results demonstrate that our algorithm can effectively resist common image processing attacks and geometric attacks, with superior robustness to other state-of-the-art algorithms.

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Acknowledgements

This work was supported by the 2021 Liaoning Provincial Natural Science Foundation Innovation Capability Enhancement Joint Fund (No: 2021-NLTS-13-01) and Liaoning Provincial Department of Education Science Foundation (Nos: JL-2004 and LJKZ1088).

Funding

Liaoning Provincial Natural Science Foundation Innovation Capability Enhancement Joint Fund, 2021-NLTS-13-01, Hongjiang Wang, Liaoning Provincial Department of Education Science Foundation, JL-2004, Hongjiang Wang, LJKZ1088, Tingting Zhao.

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Authors and Affiliations

  1. College of Information, Shenyang Institute of Engineering, Shenyang, 110136, China

    Hongjiang Wang & Tingting Zhao

  2. Public Infrastructure Department, Shenyang Conservatory of Music, Shenyang, 110818, China

    Yan Chen

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  1. Hongjiang Wang
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  2. Yan Chen
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  3. Tingting Zhao
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Correspondence to Hongjiang Wang.

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Wang, H., Chen, Y. & Zhao, T. Modified Zernike Moments and Its Application in Geometrically Resilient Image Zero-Watermarking. Circuits Syst Signal Process 41, 6844–6861 (2022). https://doi.org/10.1007/s00034-022-02076-6

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  • DOI: https://doi.org/10.1007/s00034-022-02076-6

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