DWT-SVD Combination Method for Copyrights Protection
(1) Universitas Dian Nuswantoro
(2) Universitas Dian Nuswantoro
(3) Universitas Dian Nuswantoro
(4) Universitas Dian Nuswantoro
Abstract
Many irresponsible people who download other people's artwork then modify and redistribute the work of someone without permission by not including the owner's name. Based on that problem an attempt was made to provide an invisible watermark so as not to be easy to do the watermark removal process on the artwork, using a 2-level DWT and SVD combination method that can embed watermarks invisibly and increase watermarking resistance to the image from various image manipulation processes such as noise, JPEG compression, and so on. From combination method of DWT-SVD got the highest PSNR value with watermark image size 32x32 and 64x64 which is 59.2656 dB and 54.7414 dB, respectively.
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Cong Jin, & Shu-Wei Jin. (2010). Adaptive digital image watermark scheme based on Fuzzy Neural Network for copyright protection. 2010 International Conference on Image Analysis and Signal Processing, 599–602.
Kabra, R. G., & Agrawal, S. S. (2016). Robust embedding of image watermark using LWT and SVD. International Conference on Communication and Signal Processing, ICCSP 2016, 1968–1972.
Gupta, P. (2017). Image Watermarking using IWT-SVD and its Comparative Analysis with DWT-SVD, 527–531.
Nikbakht, P., & Mahdavi, M. (2015). Targeted watermark removal of a SVD-based image watermarking scheme. 2015 7th Conference on Information and Knowledge Technology, IKT 2015, 0–5.
Ur-rehman, O., Tabatabaei, S. A. H. A. E., Zivic, N., Ruland, C., & Codes, B. R. S. (2015). Spatial and Frequency Domain Complementary Watermarks for Image Authentication and Correction, 1–6.
Panda, J., Nair, A. S., Uppal, A., & Agrawal, B. (2017). Genetic Algorithm based optimized Color Image watermarking technique using SVD and DWT, 579–583.
Deb, K., Al-Seraj, M. S., Hoque, M. M., & Sarkar, M. I. H. (2012). Combined DWT-DCT based digital image watermarking technique for copyright protection. 2012 7th International Conference on Electrical and Computer Engineering, 7, 458–461.
alama, A. S., & Mokhtar, M. A. (2016). Combined Technique for Improving Digital Image Watermarking, 2, 557–562.
Ram, B. (2013). Digital Image Watermarking Technique Using Discrete Wavelet Transform And Discrete Cosine Transform, 2(4), 19–27.
Zhou, Y., & Jin, W. (2010). An Adaptive Robust Digital Image Watermark Based on the Discrete Operation. Automatica, 2(1).
Abdallah, H. A., Hadhoud, M. M., & Shaalan, A. A. (2009). SVD-based watermarking scheme in complex wavelet domain for color video. Proceedings - The 2009 International Conference on Computer Engineering and Systems, ICCES’09, 455–460.
Mabtoul, S., Hassan, E., Elhaj, I., & Aboutajdine, D. (2007). Robust color image watermarking based on singular value decomposition and Dual tree complex wavelet transform. Multimedia Systems, 534–537.
Zhang, T.-X. Z. T.-X., Zheng, W.-M. Z. W.-M., Lu, Z.-M. L. Z.-M., & Liu, B.-B. L. B.-B. (2008). Comments on “A Semi-blind Digital Watermarking Scheme Based on Singular Value Decomposition.†2008 Eighth International Conference on Intelligent Systems Design and Applications, 2(2), 2–5.
Wei, Y., Yan, S., Yang, L., & Fu, Y. (2014). An improved median filter for removing extensive salt and pepper noise. Proceedings - 2014 International Conference on Mechatronics and Control, ICMC 2014, (Icmc), 897–901.
Li, B., Xie, W., Zhang, L., & He, Z. (2016). 3 Adaptive Fractional Integral Algorithm, 3525–3528.
Yogeswaran, A., & Payeur, P. (2017). Biasing restricted Boltzmann machines using Gaussian filters to learn invariant visual features. 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016, 0–7.
Wallace, G. K. (1992). The JPEG still picture compression standard. IEEE Transactions on Consumer Electronics, 38(1), xviii–xxxiv.
Joshi, K., Yadav, R., & Allwadhi, S. (2016). PSNR and MSE based investigation of LSB. 2016 International Conference on Computational Techniques in Information and Communication Technologies, ICCTICT 2016 - Proceedings, 280–285.
Lin, C., Hsu, K., & Hwang, J. (2014). Specific Lighting Spectrum Matching by Normalized Correlation Coefficient and Generalized Reduced Gradient Method. Specific Lighting Spectrum Matching by Normalized Correlation Coefficient and Generalized Reduced Gradient Method, 9, 470–472.
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Scientific Journal of Informatics (SJI)
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