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Recent Advances in Computer Science and Communications


ISSN (Print): 2666-2558
ISSN (Online): 2666-2566

Systematic Review Article

A Comparative Study of Various Digital Image Watermarking Techniques: Specific to Hybrid Watermarking

Author(s): Sushma Jaiswal and Manoj Kumar Pandey*

Volume 16, Issue 8, 2023

Published on: 26 June, 2023

Article ID: e220523217211 Pages: 20

DOI: 10.2174/2666255816666230522155134

Price: $65


Digital security is one of the important aspects of today’s era. Digital content is being grown every day on the internet; therefore, it is essential to guard the copyright of digital content using various techniques. Watermarking has emerged as an important field of study aiming at securing digital content and copyright protection. None of the watermarking techniques can provide well robustness against all the attacks, and algorithms are designed based on required specifications, which means there is a lot of opportunity in this field. Image watermarking is a vast area of research, starting from spatial-based methods to deep learning-based methods, and it has recently gained a lot of popularity due to the involvement of deep learning technology for ensuring the security of digital content. This study aims at exploring important highlights from spatial to deep learning methods of watermarking, which will be helpful for the researchers. In order to accomplish this study, the standard research papers of the last ten years have been obtained from various databases and reviewed to answer the five research questions. Open issues and challenges are identified and listed after reviewing various kinds of literature. Our study reveals that hybrid watermarking performs better in terms of balancing the trade-off between imperceptibility and robustness. Current research trends and future direction is also discussed.

Keywords: DCT, DWT, LWT, CNN, machine learning, watermarking.

Graphical Abstract
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