Digital image watermarking using DWT-SVD with enhanced tunicate swarm optimization algorithm
Image watermarking is the vital process in leveraging digital rights management for valuable intellectual properties. Recently, large number of works was found out to build the image watermarking efficiency in order to cater to the security demands of content protection. However, it is essential to...
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| Published in | Multimedia tools and applications Vol. 82; no. 18; pp. 28259 - 28279 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Springer US
01.07.2023
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1380-7501 1573-7721 |
| DOI | 10.1007/s11042-023-14618-4 |
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| Abstract | Image watermarking is the vital process in leveraging digital rights management for valuable intellectual properties. Recently, large number of works was found out to build the image watermarking efficiency in order to cater to the security demands of content protection. However, it is essential to take into account the robustness of watermarking methods. Therefore, robust image watermarking techniques are introduced to show robustness against various attacks and other issues in watermarking. In this paper, a digital image watermarking technique based on Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) is proposed. The DWT and SVD methods are hybridized to enhance the embedding capacity. Based on the low variance calculation, optimal image blocks are selected by the Enhanced Tunicate Swarm Algorithm. TSA optimization is enhanced by the optimization of Sine Cosine Algorithm which is used to update the optimal solution of low variance value. Before embedding, the watermark is scrambled by Arnold scrambling and Tent Map chaotic encryption for double layer security to the watermark image. After embedding, the extraction process is carried out. The experiments are conducted on Pepper, Barbara, Lena, Baboon and Airplane image sets. The results are compared with different watermarking approaches and optimization approaches in terms of Peak Signal to Noise ratio (PSNR), Normalization Correlation (NC), and Structural Similarity Index Measure (SSIM). To show the robustness, the proposed method is evaluated under various geometric attacks and found to achieve better accuracy and robustness compared to existing methods. |
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| AbstractList | Image watermarking is the vital process in leveraging digital rights management for valuable intellectual properties. Recently, large number of works was found out to build the image watermarking efficiency in order to cater to the security demands of content protection. However, it is essential to take into account the robustness of watermarking methods. Therefore, robust image watermarking techniques are introduced to show robustness against various attacks and other issues in watermarking. In this paper, a digital image watermarking technique based on Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) is proposed. The DWT and SVD methods are hybridized to enhance the embedding capacity. Based on the low variance calculation, optimal image blocks are selected by the Enhanced Tunicate Swarm Algorithm. TSA optimization is enhanced by the optimization of Sine Cosine Algorithm which is used to update the optimal solution of low variance value. Before embedding, the watermark is scrambled by Arnold scrambling and Tent Map chaotic encryption for double layer security to the watermark image. After embedding, the extraction process is carried out. The experiments are conducted on Pepper, Barbara, Lena, Baboon and Airplane image sets. The results are compared with different watermarking approaches and optimization approaches in terms of Peak Signal to Noise ratio (PSNR), Normalization Correlation (NC), and Structural Similarity Index Measure (SSIM). To show the robustness, the proposed method is evaluated under various geometric attacks and found to achieve better accuracy and robustness compared to existing methods. |
| Author | Kumari, Ms R. Radha Naidu, K. Rama Kumar, V. Vijaya |
| Author_xml | – sequence: 1 givenname: Ms R. Radha orcidid: 0000-0002-7834-6939 surname: Kumari fullname: Kumari, Ms R. Radha email: radharavada999@gmail.com organization: Department of Electronics and Communication Engineering, Jawaharlal Nehru Technological University Ananthpuramu – sequence: 2 givenname: V. Vijaya surname: Kumar fullname: Kumar, V. Vijaya organization: Department of CSE and Dean Research and Development, Anurag University – sequence: 3 givenname: K. Rama surname: Naidu fullname: Naidu, K. Rama organization: Department of Electronics and Communication Engineering, Jawaharlal Nehru Technological University Ananthpuramu |
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| CitedBy_id | crossref_primary_10_1177_20427530241239410 crossref_primary_10_1007_s11831_025_10228_5 crossref_primary_10_1080_1206212X_2024_2408748 |
| Cites_doi | 10.1007/s11042-019-7650-0 10.1007/s13042-015-0329-6 10.1080/09720529.2020.1721875 10.1016/j.dsp.2021.103130 10.1109/ACCESS.2020.2988298 10.1016/j.aeue.2012.12.001 10.1109/TCSVT.2019.2960507 10.1007/978-981-10-8863-6_19 10.1016/j.ins.2018.03.040 10.1109/ACCESS.2020.3024181 10.1155/2018/5325040 10.1109/ACCESS.2021.3104985 10.1007/s11220-020-00291-6 10.1016/S1665-6423(14)71612-8 10.1007/s11042-018-6177-0 10.1109/TCSVT.2016.2633878 10.1007/978-3-319-57699-2 10.1016/j.sigpro.2016.12.010 10.1016/j.sigpro.2018.11.011 10.1109/ACCESS.2021.3060861 10.1016/j.sigpro.2019.06.025 10.1007/s00500-018-3535-9 10.1109/ACCESS.2021.3058128 10.1016/j.sigpro.2020.107864 10.1016/j.ins.2018.08.028 10.1155/2022/5271600 10.5120/21212-3915 10.1016/j.engappai.2020.103541 10.1007/s11042-020-10028-y 10.1016/j.image.2016.03.007 10.1007/s13735-020-00197-9 10.1109/ACCESS.2018.2808172 |
| ContentType | Journal Article |
| Copyright | The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| Keywords | Image security Image watermarking Enhanced tunicate swarm algorithm Block variance and Arnold scrambling |
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| SubjectTerms | Algorithms Computer Communication Networks Computer Science Copy protection Data Structures and Information Theory Digital imaging Digital watermarking Discrete Wavelet Transform Embedding Image enhancement Multimedia Information Systems Optimization Robustness Scrambling (communication) Security Signal to noise ratio Singular value decomposition Special Purpose and Application-Based Systems Trigonometric functions Wavelet transforms |
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| Title | Digital image watermarking using DWT-SVD with enhanced tunicate swarm optimization algorithm |
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