A new zero-watermarking algorithm based on deep learning
Jing Liu, Qiannan Li, Hui Yang · Fourteenth International Conference on Digital Image Processing (ICDIP 2022) · 2022
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.