Convolutional Autoencoders-Based Image Watermarking Techniques
Shikha Yadav, Jeevan Bala · 2023
Digital image watermarking plays an important role in securing multimedia content against unauthorized use and manipulation. The realm of image watermarking focuses on its vulnerability to various attacks and the integration of Convolutional Neural Networks (CNNs) to bolster its robustness. This proposed paper illustrates an overview of common attacks such as geometric transformations, compression, and signal processing attacks, which can compromise watermark robustness and integrity. These findings highlight the effectiveness and reliability of the encoder, embedder, decoder, and extractor modules in achieving secure and visually appealing watermarking.