Proceedings of the 6th International Conference on Deep Learning, Artificial Intelligence and Robotics (ICDLAIR 2024)

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A Robust Watermarking Approach for Securing Copyright in Watershed Images

Authors
Harendra Singh1, *, Maroti Deshmukh1, *, Lalit Kumar Awasthi2, Krishan Berwal3
1National Institute of Technology, Uttarakhand, India
2Sardar Patel University, Mandi, India
3Military College of Telecommunication Engineering, Mhow, India
*Corresponding author. Email: harendra.singhphd2021@nituk.ac.in
*Corresponding author. Email: marotideshmukh@nituk.ac.in
Corresponding Authors
Harendra Singh, Maroti Deshmukh
Available Online 25 June 2025.
DOI
10.2991/978-94-6463-740-3_27How to use a DOI?
Keywords
Watershed images; Copyright Protection; Watermarking; Security
Abstract

Watershed images are essential for environmental resource management, providing critical insights into hydrological and ecological systems. However, these images are vulnerable to unauthorized access, misuse, and copyright violations during digital transmission and storage. This paper presents a robust approach combining Discrete Wavelet Transform (DWT), Hessenberg Decomposition (HD), and Randomized Singular Value Decomposition (RSVD) to conceal the user’s Aadhar Card details into watershed images for copyright protection and authentication. Additionally, an encryption scheme enhances protection against tampering and unauthorized access, making it suitable for cloud-based storage solutions. Experimental results reveal that the proposed algorithm achieves satisfactory performance, including PSNR up to 40.12 dB, SSIM near 1, and NC up to 0.9934. The comparative analysis demonstrates the proposed method’s strength over existing techniques, offering a reliable solution for copyright protection, identity verification, and secure cloud storage of watershed images.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 6th International Conference on Deep Learning, Artificial Intelligence and Robotics (ICDLAIR 2024)
Series
Advances in Intelligent Systems Research
Publication Date
25 June 2025
ISBN
978-94-6463-740-3
ISSN
1951-6851
DOI
10.2991/978-94-6463-740-3_27How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Harendra Singh
AU  - Maroti Deshmukh
AU  - Lalit Kumar Awasthi
AU  - Krishan Berwal
PY  - 2025
DA  - 2025/06/25
TI  - A Robust Watermarking Approach for Securing Copyright in Watershed Images
BT  - Proceedings of the 6th International Conference on Deep Learning, Artificial Intelligence and Robotics (ICDLAIR 2024)
PB  - Atlantis Press
SP  - 314
EP  - 323
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-740-3_27
DO  - 10.2991/978-94-6463-740-3_27
ID  - Singh2025
ER  -