Robust Digital Watermarking based on Machine Learning
Manish Rai, Hemlata Hemlata · 2023
In the generation of big data and systems administration, it is important to build up a safe and strong digital watermarking plan with high computational effectiveness to ensure copyrights of digital works. However, the greater part of the current strategies focuses on robustness and embedding limit, losing a security, or requiring huge computational assets in the encryption procedure. Digital watermarking has become an important method for ensuring the security of digital copyrights and ensuring the authenticity of data because of rapid advancement and broad usage of technologies related to multimedia and network connectivity. which has been used for practical application such as medical application, currency, digital product identification and many more. The success story of digital watermarking techniques deepened on the embedding of the watermark image and present image. In the current decade, the machine learning feature-based watermarking techniques create new milestone concerning security concern. The machine learning and hybrid digital watermarking performances an especially vital role in optimization and selection of features which improves the performance of watermarking process. In this paper, we have presented countless digital watermarking, methods which is based on various machine learning procedures along with their comparison, and limitation.