Implementation of Image Watermark Algorithm Based on FPGAImage watermark embedding circuit
Authors: 
Guotao Cong, Sen Wang, Henan LiAuthors Info & Claims
Guotao Cong, Sen Wang, Henan LiAuthors Info & ClaimsPages 277 - 282
Abstract
With the popularization of the Internet and the widespread application of digital technology, there are more and more digital products that are easy to spread, and at the same time, copyright protection issues are becoming increasingly prominent. Digital watermarking technology has been continuously developed in this context. This system is based on the FPGA platform to embed image watermarks and achieve hardware acceleration processing. Receive the data of the original image and watermark image through the high-speed transmission interface, perform wavelet transform on the original image, embed the watermark image, and then output the synthesized watermark image data through the high-speed transmission interface. This system selects the lifting wavelet transform algorithm as the watermark embedding algorithm to achieve blind watermarking, which has the characteristics of easy hardware implementation, high robustness and security of the watermark. The system has been verified through simulation and physical testing, with correct functionality and reliable performance.
References
[1]
C. Dai. 2022. Analysis on Digital Watermarking Technology and Its Applications. In Proceedings of 2022 International Conference on Data Analytics, Computing and Artificial Intelligence (ICDACAI). IEEE, 200-204. https://doi.org/10.1109/ICDACAI57211. 2022.00048.
[2]
B. K. Yakti, S. Madenda, S. A. Sudiro and P. Musa. 2021. Processing Speed Comparison of the Least Significant Bit (LSB) Steganography Algorithm on FPGA and Matlab. In Proceedings of 2021 Sixth International Conference on Informatics and Computing (ICIC). IEEE, 1-7. https://doi.org/10.1109/ICIC54025. 2021.9632978.
[3]
U. Tuba and D. Zivkovic. 2021. Image Denoising by Discrete Wavelet Transform with Edge Preservation. In Proceedings of 2021 13th International Conference on Electronics, Computers and Artificial Intelligence (ECAI). IEEE., 1-4. https://doi.org/10.1109/ECAI52376. 2021.9515079.
[4]
W. Wang, Y. Ning, Y. Hu and Y. Yang. 2019. Research on a Digital Watermarking Algorithm for Color Image Based on Dual-Tree Complex Wavelet Transform (DTCWT). In Proceedings of 2019 2nd World Conference on Mechanical Engineering and Intelligent Manufacturing (WCMEIM). IEEE, 443-446. https://doi.org/10.1109/WCMEIM48965. 2019.00093.
[5]
N. Aissaoui, M. S. Azzaz and R. Kaibou. 2022. FPGA Implementation of a Digital Watermarking System using dwt Transformation. In Proceedings of 2022 2nd International Conference on Advanced Electrical Engineering (ICAEE). IEEE, 1-5. https://doi.org/10.1109/ICAEE53772. 2022.9962026.
Index Terms
- Implementation of Image Watermark Algorithm Based on FPGAImage watermark embedding circuit
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Published In
December 2023
467 pages
ISBN:9798400716966
DOI:10.1145/3661638
Copyright © 2023 ACM.
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Association for Computing Machinery
New York, NY, United States
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Published: 01 June 2024
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AISNS 2023
AISNS 2023: 2023 International Conference on Artificial Intelligence, Systems and Network Security
December 22 - 24, 2023
Mianyang, China
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