A Novel Framework for Digital Image Watermarking Based on Neural Network

Abstract

There are many instances of intellectual property rights violations due to the common usage of digital data on the Internet, including unauthorised use, copying, and theft of digital content. Intellectual property rights of digital photos must be upheld, as they are very valuable materials. Digital watermarking is a more modern method to do this. By using a watermark (WM), the owner's information is included into the content, which may then be shared or saved. When required, this technology will retrieve the encoded WM information to prove ownership. Different technologies have been investigated and created on the basis of existing technologies, fields of use, etc. This paper proposes a novel approach to digital watermarking based on a neural network. First, the trigger data set and noise data set are generated from the binary encoding and random cutting of the original training samples. Then, the pattern with higher watermark trigger accuracy is obtained from the trigger set. Simulation results show that the proposed algorithm performs better in terms of accuracy and computing time cost compared to existing algorithms