Applicability of various transform techniques in watermarking using Machine Learning Algorithm - A Systematic Analysis
Naman Garg, Laxmanika · Procedia Computer Science · 2025
The expansion of multimedia data, particularly images, and videos from intellectual devices and sensors, has led to augmented concerns about illegal access and fraudulent usage. Digital watermarking embeds a watermark into digital media and later extracts it, and offers a proposal to ownership and copyright matters to protect authorized data. A thorough analysis of watermarking with popular technologies like deep learning, machine learning, and artificial intelligence is presented in this article. Furthermore, it covers general information, the extremely innovative and popular applications, and the introduction of watermarking in brief. The inclusion of machine learning methods has led to significant in the execution of the watermarking system. Machine learning models can discover complex patterns and features from large datasets, enabling the development of watermarking algorithms that are more robust to attack and distortions. This review comprehensively examines digital watermarking techniques within Machine Learning environments. This paper covers the fundamentals of traditional and learningbased watermarking to explore popular Machine Learning models used in watermarking, summarizes recent contributions in the literature, and guides the challenges and future research directions in the field.