Compression Run Length Encoding On Watermarking Using a Combination of DCT, DWT and SVD
DOI:
https://doi.org/10.33633/jais.v8i2.7524Abstract
This study focus on identifying medical images by proposing the Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT) and Singular Value Decomposition (SVD) transformation watermarking technique and prove an increase the quality of watermarked images is good in terms of imperceptibility. Due to reduce the need for data memory compression is applied to the host image, where the compression technique chosen is lossless so that the compressed host image experiences a decrease in file size while maintaining data integrity, to maintain image degradation perceptions and diagnostic quality standards during the watermarking process. Here, we use DWT-DCT-SVD and Run Length Encoding (RLE). A good Peak Signal to Noise Ratio (PSNR) more than 30 dB using over than 200 compression size. The extracted watermark image is quite good with a fairly high PSNR value. The highest compression result size is in 32.2511.References
S. Singh, V. S. Rathore, R. Singh, and M. K. Singh, “Hybrid semi-blind image watermarking in redundant wavelet domain,” Multimed. Tools Appl., vol. 76, no. 18, pp. 19113–19137, Sep. 2017.
M. Pravin Savaridass, R. Deepika, R. Aarnika, V. Maniraj, P. Gokilanandhi, and K. Kowsika, “Digital Watermarking For Medical Images Using Dwt And Svd Technique,” IOP Conf. Ser. Mater. Sci. Eng., vol. 1084, no. 1, p. 012034, 2021.
A. Soualmi, A. Alti, and L. Laouamer, “A New Blind Medical Image Watermarking Based on Weber Descriptors and Arnold Chaotic Map,” Arab. J. Sci. Eng., vol. 43, no. 12, pp. 7893–7905, Dec. 2018.
O. Y. Abdulhammed, “Improving Encryption Digital Watermark by Using Blue Monkey Algorithm,” Int. J. Comput., vol. 20, no. 1, pp. 129–136, 2021.
N. N. Hurrah, S. A. Parah, and J. A. Sheikh, “Embedding in medical images: an efficient scheme for authentication and tamper localization,” Multimed. Tools Appl., vol. 79, no. 29–30, pp. 21441–21470, Aug. 2020.
E. H. Rachmawanto, C. Atika Sari, and R. P. Pradana, “DWT-SVD Combination Method for Copyrights Protection,” Sci. J. Informatics, vol. 7, no. 1, pp. 113–124, 2020.
A. Shukla and S. Kumar, “Analysis of secure watermarking based on DWT-SVD technique for piracy,” in 2016 International Conference on Computing, Communication and Automation (ICCCA), 2016, pp. 1110–1115.
A. Anand and A. K. Singh, “An improved DWT-SVD domain watermarking for medical information security,” Comput. Commun., vol. 152, no. January, pp. 72–80, 2020.
C. A. Sari, E. H. Rachmawanto, and D. R. I. M. Setiadi, “Robust and imperceptible image watermarking by dc coefficients using singular value decomposition,” in International Conference on Electrical Engineering, Computer Science and Informatics (EECSI), 2017, vol. 4.
T. A. B. W, Adiwijaya, and F. P. Permana, “Medical Image Watermarking with Tamper Detection and Recovery Using Reversible Watermarking with LSB Modification and Run Length Encoding (RLE) Compression,” 2012, pp. 167–171.
K. Fares, A. Khaldi, K. Redouane, and E. Salah, “DCT & DWT based watermarking scheme for medical information security,” Biomed. Signal Process. Control, vol. 66, no. August 2020, p. 102403, Apr. 2021.
A. A. A. Hadad, H. N. Khalid, Z. S. Naser, and M. S. Taha, “A Robust Color Image Watermarking Scheme Based on Discrete Wavelet Transform Domain and Discrete Slantlet Transform Technique,” Ing. des Syst. d’Information, vol. 27, no. 2, pp. 313–319, 2022.
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.
M. Begum, J. Ferdush, and M. S. Uddin, “A Hybrid robust watermarking system based on discrete cosine transform, discrete wavelet transform, and singular value decomposition,” J. King Saud Univ. - Comput. Inf. Sci., vol. 34, no. 8, pp. 5856–5867, 2022.
A. A.-A. Hadad, H. N. Khalid, Z. S. Naser, and M. S. Taha, “A Robust Color Image Watermarking Scheme Based on Discrete Wavelet Transform Domain and Discrete Slantlet Transform Technique,” Ingénierie des systèmes d Inf., vol. 27, no. 2, pp. 313–319, Apr. 2022.
K. Deb, M. S. Al-Seraj, M. M. Hoque, and M. I. H. Sarkar, “Combined DWT-DCT based digital image watermarking technique for copyright protection,” in 2012 7th International Conference on Electrical and Computer Engineering, 2012, pp. 458–461.
O. Hosam and N. Ben Halima, “A hybrid ROI-embedding based watermarking technique using DWT and DCT transforms,” J. Theor. Appl. Inf. Technol., vol. 81, no. 3, pp. 514–528, 2015.
A. Winarno, S. D.R.I.M, A. A. Arrasyid, C. A. Sari, and E. H. Rachmawanto, “Image Watermarking using Low Wavelet Subband based on 8x8 Sub-block DCT,” in International Seminar on Application for Technology of Information and Communication, 2017, pp. 11–15.
Z. Li, H. Zhang, X. Liu, C. Wang, and X. Wang, “Blind and safety-enhanced dual watermarking algorithm with chaotic system encryption based on RHFM and DWT-DCT,” Digit. Signal Process., vol. 115, p. 103062, Aug. 2021.
Y.-L. Bei, S. Qiao, M.-X. Liu, X.-R. Zhu, and Q. Zhang, “A Color Image Watermarking Scheme Against Geometric Rotation Attacks Based on HVS and DCT-DWT,” in 2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC), 2018, pp. 343–347.
Falgun Thakkar and V. K. Srivastava, “An adaptive, secure and imperceptive image watermarking using swarm intelligence, Arnold transform, SVD and DWT,” Multimed. Tools Appl., vol. 80, no. 8, pp. 12275–12292, Mar. 2021.
N. Ben Halima, M. A. Khan, and R. Kumar, “A Novel Approach of Digital Image Watermarking using HDWT-DCT,” in 2015 Global Summit on Computer & Information Technology (GSCIT), 2015, no. June, pp. 1–6.
S. Gaur and V. K. Srivastava, “A hybrid RDWT-DCT and SVD based digital image watermarking scheme using Arnold transform,” in 2017 4th International Conference on Signal Processing and Integrated Networks (SPIN), 2017, pp. 399–404.
Z. Nana, “Watermarking algorithm of spatial domain image based on SVD,” in 2016 International Conference on Audio, Language and Image Processing (ICALIP), 2016, no. 4, pp. 361–365.
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