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Vol. 8, No. 4, November 2023

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This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Discrete Cosine Transform and Singular Value Decomposition Based on Canny Edge Detection for Image Watermarking

https://doi.org/10.22219/kinetik.v8i4`.1768
Erna Zuni Astuti
Universitas Dian Nuswantoro
Christy Atika Sari
Universitas Dian Nuswantoro
https://orcid.org/0000-0002-7296-5210
Eko Hari Rachmawanto
Universitas Dian Nuswantoro
Yani Parti Astuti
Universitas Dian Nuswantoro
Harwinanda Oktaridha
Universitas Dian Nuswantoro
Folasade Olubusola Isinkaye
Ekiti State University

Corresponding Author(s) : Christy Atika Sari

christya.atika.sari@dsn.dinus.ac.id

Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, Vol. 8, No. 4, November 2023

Abstract

The development of an increasingly sophisticated internet allows for the distribution of digital images that can be done easily. However, with the development of increasingly sophisticated internet networks, it becomes an opportunity for some irresponsible people to misuse digital images, such as taking copyrights, modification and duplicating digital images. Watermarking is an information embedding technique to show ownership descriptions that can be conveyed into text, video, audio, and digital images. There are 2 groups of watermarking based on their working domain, namely the spatial domain and the transformation domain. In this study, three domain transformation techniques were used, namely Singular Value Descomposition (SVD), Discrete Cosine Transform (DCT) and Canny Edge Detection Techniques. The proposed attacks are rotation, gaussian blurness, salt and pepper, histogram equalization, and cropping. The results of the experiment after inserting the watermark image were measured by the Peak Signal to Noise Ratio (PSNR). The results of the image robustness test were measured by the Correlation Coefficient (Corr) and Normalized Correlation (NC). The analysis and experimental results show that the results of image extraction are good with PSNR values from watermarked images above 50dB and Corr values reaching 0.95. The NC value obtained is also high, reaching 0.98. Some of the extracted images are of fairly good quality and are similar with the original image.

Keywords

Image Watermarking Discrete Cosine Transform Singular Value Decomposition Canny Edge Detection Grayscale
Astuti, E. Z., Sari, C. A., Rachmawanto, E. H., Astuti, Y. P., Oktaridha, H., & Isinkaye, F. O. (2023). Discrete Cosine Transform and Singular Value Decomposition Based on Canny Edge Detection for Image Watermarking . Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, 8(4`). https://doi.org/10.22219/kinetik.v8i4`.1768
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References
  1. H.-J. Ko, C.-T. Huang, G. Horng, and S.-J. WANG, “Robust and blind image watermarking in DCT domain using inter-block coefficient correlation,” Inf Sci (N Y), vol. 517, pp. 128–147, May 2020. https://doi.org/10.1016/j.ins.2019.11.005
  2. N. Zermi, A. Khaldi, M. R. Kafi, F. Kahlessenane, and S. Euschi, “Robust SVD-based schemes for medical image watermarking,” Microprocess Microsyst, vol. 84, p. 104134, Jul. 2021. https://doi.org/10.1016/j.micpro.2021.104134
  3. X. Wang, K. Hu, J. Hu, L. Du, A. T. S. Ho, and H. Qin, “Robust and blind image watermarking via circular embedding and bidimensional empirical mode decomposition,” Vis Comput, vol. 36, no. 10–12, pp. 2201–2214, Oct. 2020. https://doi.org/10.1007/s00371-020-01909-2
  4. S. B. B. Ahmadi, G. Zhang, M. Rabbani, L. Boukela, and H. Jelodar, “An intelligent and blind dual color image watermarking for authentication and copyright protection,” Applied Intelligence, vol. 51, no. 3, pp. 1701–1732, Mar. 2021. https://doi.org/10.1007/s10489-020-01903-0
  5. X. Wang, D. Ma, K. Hu, J. Hu, and L. Du, “Mapping based Residual Convolution Neural Network for Non-embedding and Blind Image Watermarking,” Journal of Information Security and Applications, vol. 59, p. 102820, Jun. 2021. https://doi.org/10.1016/j.jisa.2021.102820
  6. N. Hasan, M. S. Islam, W. Chen, M. A. Kabir, and S. Al-Ahmadi, “Encryption Based Image Watermarking Algorithm in 2DWT-DCT Domains,” Sensors, vol. 21, no. 16, p. 5540, Aug. 2021. https://doi.org/10.3390/s21165540
  7. L. B. Handoko, Utariyanto, D. R. I. M. Setiadi, E. H. Rachmawanto, C. A. Sari, and R. R. Ali, “An Analysis of Imperceptibility and Robustness Performance in CRT Image Watermarking based on Color Space Theory,” J Phys Conf Ser, vol. 1501, no. 1, p. 012015, Mar. 2020. https://doi.org/10.1088/1742-6596/1501/1/012015
  8. X. Kang, Y. Chen, F. Zhao, and G. Lin, “Multi-dimensional particle swarm optimization for robust blind image watermarking using intertwining logistic map and hybrid domain,” Soft comput, vol. 24, no. 14, pp. 10561–10584, Jul. 2020. https://doi.org/10.1007/s00500-019-04563-6
  9. R. Sinhal, S. Sharma, I. A. Ansari, and V. Bajaj, “Multipurpose medical image watermarking for effective security solutions,” Multimed Tools Appl, vol. 81, no. 10, pp. 14045–14063, Apr. 2022. https://doi.org/10.1007/s11042-022-12082-0
  10. C. A. Sari, Utariyanto, D. R. I. M. Setiadi, E. H. Rachmawanto, and M. K. Sarker, “Robust IHWT- CRT Image Watermarking using YCbCr Color Space,” J Phys Conf Ser, vol. 1501, no. 1, p. 012014, Mar. 2020. https://doi.org/10.1088/1742-6596/1501/1/012014
  11. D. K. Mahto and A. K. Singh, “A survey of color image watermarking: State-of-the-art and research directions,” Computers & Electrical Engineering, vol. 93, p. 107255, Jul. 2021. https://doi.org/10.1016/j.compeleceng.2021.107255
  12. P. Kadian, S. M. Arora, and N. Arora, “Robust Digital Watermarking Techniques for Copyright Protection of Digital Data: A Survey,” Wirel Pers Commun, vol. 118, no. 4, pp. 3225–3249, Jun. 2021. https://doi.org/10.1007/s11277-021-08177-w
  13. Y. A. Mekarsari, D. Setiadi, C. A. Sari, E. H. Rachmawanto, and Muljono, “Non-Blind RGB Image Watermarking Technique using 2-Level Discrete Wavelet Transform and Singular Value Decomposition,” in International Conference on Information and Communications Technology (ICOIACT), 2018, pp. 623–627. https://doi.org/10.1109/ICOIACT.2018.8350793
  14. C. A. Sari, E. H. Rachmawanto, and D. Setiadi, “Robust and Imperceptible Image Watermarking by DC Coefficients Using Singular Value Decomposition,” in International Conference on Electrical Engineering, Computer Science and Informatics, IEEE, 2017. https://doi.org/10.1109/EECSI.2017.8239107
  15. E. H. Rachmawanto, D. R. I. M. Setiadi, C. A. Sari, and N. Rijati, “Imperceptible and secure image watermarking using DCT and random spread technique,” TELKOMNIKA (Telecommunication Computing Electronics and Control), vol. 17, no. 4, p. 1750, Aug. 2019. http://doi.org/10.12928/telkomnika.v17i4.9227
  16. A. A. Arrasyid, D. Setiadi, M. A. Soeleman, C. A. Sari, and E. H. Rachmawanto, “Image Watermarking using Triple Transform (DCT-DWT-SVD) to Improve Copyright Protection Performance,” in International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), 2018, pp. 522–526. https://doi.org/10.1109/ISRITI.2018.8864461
  17. E. L. Lydia, J. S. Raj, R. Pandi Selvam, M. Elhoseny, and K. Shankar, “Application of discrete transforms with selective coefficients for blind image watermarking,” Transactions on Emerging Telecommunications Technologies, vol. 32, no. 2, Feb. 2021. https://doi.org/10.1002/ett.3771
  18. A. Susanto, D. Setiadi, E. H. Rachmawanto, I. U. Mulyono, and C. A. Sari, “An Improve Image Watermarking using Random Spread Technique and Discrete Cosine Transform,” in International Conference on Information and Communications Technology (ICOIACT, 2019, pp. 168–173. https://doi.org/10.1109/ICOIACT46704.2019.8938498
  19. P. Garg and R. R. Kishore, “An efficient and secured blind image watermarking using ABC optimization in DWT and DCT domain,” Multimed Tools Appl, vol. 81, no. 26, pp. 36947–36964, Nov. 2022. https://doi.org/10.1007/s11042-021-11237-9
  20. N. Zermi, A. Khaldi, R. Kafi, F. Kahlessenane, and S. Euschi, “A DWT-SVD based robust digital watermarking for medical image security,” Forensic Sci Int, vol. 320, p. 110691, Mar. 2021. https://doi.org/10.1016/j.forsciint.2021.110691
  21. A. A. Mohammed, D. A. Salih, A. M. Saeed, and M. Q. Kheder, “An imperceptible semi-blind image watermarking scheme in DWT-SVD domain using a zigzag embedding technique,” Multimed Tools Appl, vol. 79, no. 43–44, pp. 32095–32118, Nov. 2020. https://doi.org/10.1007/s11042-020-09694-9
  22. Sunesh and R. R. Kishore, “A Novel and Efficient Blind Image Watermarking In Transform Domain,” Procedia Comput Sci, vol. 167, pp. 1505–1514, 2020. https://doi.org/10.1016/j.procs.2020.03.361
  23. S. P. Vaidya, “Fingerprint-based robust medical image watermarking in hybrid transform,” Vis Comput, vol. 39, no. 6, pp. 2245–2260, Jun. 2023. https://doi.org/10.1007/s00371-022-02406-4
  24. F. Kahlessenane, A. Khaldi, M. R. Kafi, and S. Euschi, “A color value differentiation scheme for blind digital image watermarking,” Multimed Tools Appl, vol. 80, no. 13, pp. 19827–19844, May 2021. https://doi.org/10.1007/s11042-021-10713-6
  25. E. Kartikadarma, E. D. Udayanti, C. A. Sari, and M. Doheir, “A Comparison of Non Blind Image Watermarking Using Transformation Domain,” Scientific Journal of Informatics, vol. 8, no. 1, 2021. https://doi.org/10.15294/sji.v8i1.28334
  26. F. Kahlessenane, A. Khaldi, R. Kafi, and S. Euschi, “A robust blind medical image watermarking approach for telemedicine applications,” Cluster Comput, vol. 24, no. 3, pp. 2069–2082, Sep. 2021. https://doi.org/10.1007/s10586-020-03215-x
  27. A. M. Cheema, S. M. Adnan, and Z. Mehmood, “A Novel Optimized Semi-Blind Scheme for Color Image Watermarking,” IEEE Access, vol. 8, pp. 169525–169547, 2020. https://doi.org/10.1109/ACCESS.2020.3024181
  28. Z. Yuan, Q. Su, D. Liu, and X. Zhang, “A blind image watermarking scheme combining spatial domain and frequency domain,” Vis Comput, vol. 37, no. 7, pp. 1867–1881, Jul. 2021. https://doi.org/10.1007/s00371-020-01945-y
  29. Z. Bin Faheem et al., “Image Watermarking Using Least Significant Bit and Canny Edge Detection,” Sensors, vol. 23, no. 3, p. 1210, Jan. 2023. https://doi.org/10.3390/s23031210
  30. S. Y. Chilkandi Mtech, M. Moodbidri, and N. U. Banu M Asst professor, “Digital Image Watermarking Based On Canny Edge Detection and Texture Block in DWT,” International Journal of Research and Engineering, vol. 1, no. 4.
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