A Robust Image Zero-watermarking using Convolutional Neural Networks
Atoany Nazareth Fierro-Radilla, Mariko Nakano-Miyatake, Manuel Cedillo-Hernández, L. Cleofas-Sánchez, Hector Manuel Perez-Meana · 2019
In the image zero-watermarking techniques, a watermark sequence is not physically embedded into the host image but has a logical linkage with the host image. This property of zero-watermarking is desirable for some kinds of images in which a minimum distortion may cause serious detection or diagnostic errors, such as medical images and remote sensing images. In this paper, we propose a robust zero-watermarking algorithm based on the Convolutional Neural Networks (CNN) and deep learning algorithm, in which robust inherent features of image is generated by the CNN, and it is combined with the owner's watermark sequence using XOR operation. The experimental results show the watermark robustness against several attacks and common image processing.