A new zero-watermarking algorithm based on deep learning

Jing Liu; Qiannan Li; Hui Yang

doi:10.1117/12.2643017

12 October 2022 A new zero-watermarking algorithm based on deep learning

Jing Liu, Qiannan Li, Hui Yang

Proceedings Volume 12342, Fourteenth International Conference on Digital Image Processing (ICDIP 2022); 123422T (2022) https://doi.org/10.1117/12.2643017
Event: Fourteenth International Conference on Digital Image Processing (ICDIP 2022), 2022, Wuhan, China

Abstract

A new zero-watermarking algorithm based on deep learning is proposed to improve the robustness of the zero-watermarking, in which zero-watermarking image generation and copyright verification are both completed using neural networks. First, a stylized image is generated from a host image and a logo image with a time stamp through VGG network. Then, the stylized image is encrypted by the Arnold transform and registered as a zero-watermarking image in Intellectual Property Protection (IPR). Finally, the RCNN network is designed to extract the logo image to verify the copyright of host images. The experimental results show that the security and robustness of the algorithm are better than the existing zero-watermarking algorithm.

Citation Download Citation

Jing Liu, Qiannan Li, and Hui Yang "A new zero-watermarking algorithm based on deep learning", Proc. SPIE 12342, Fourteenth International Conference on Digital Image Processing (ICDIP 2022), 123422T (12 October 2022); https://doi.org/10.1117/12.2643017

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KEYWORDS

Digital watermarking

Image segmentation

Image encryption

Image compression

Convolutional neural networks

Quantization

Feature extraction

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