Exploring The Robustness Of Digital Watermarking Algorithms Based On Transform Function And Machine Learning

Abstract

The robustness of digital watermarking algorithms is a critical factor for analysing the security of digital multimedia. The increasing utility of digital multimedia in every filed area of business needed copyright protection. Copyright protection is the intergluteal property of digital assets. The strength of robustness used various algorithms and methods in current research trends of digital data security. This paper explores the robustness of digital image watermarking using transform function and machine learning. The machine learning-based digital watermarking techniques uplift the strength of security. The machine learning algorithm's primary issue is the transformation and mapping of digital image data for the conversion of digital image data using the process of transform function. The utility of the transform function is very high in the area of image processing. The transform function is directly applied in image compression, pattern recognition, and many more. In digital watermarking, the transform function provides security and compression of data—the combination of transform function and machine learning born a new dimension of digital image watermarking. The analysis of watermarking algorithms used MATLAB software and reputed image data based on empirical parameters for performance.