A Novel Watermarking Method using Hadamard Matrix Quantization
DOI:
https://doi.org/10.5614/itbj.ict.res.appl.2020.14.1.1Keywords:
Hadamard matrix, image processing, quantization, SVD, watermarkingAbstract
One of the most used watermarking algorithms is Singular Value Decomposition (SVD), which has a balanced level of imperceptibility and robustness. However, SVD uses a singular matrix for embedding and two orthogonal matrices for reconstruction, which is inefficient. In this paper, a Hadamard matrix is used to get a singular matrix for the reconstruction process. Moreover, SVD works with a floating-point value, which takes long processing time, while the Hadamard matrix works with an integer range, which is more efficient. Visual measurement showed that SVD and the new method had average NC values of 0.8321 and 0.8293, whereas the average SSIM values resulted in the same value (0.9925). In terms of processing time, the proposed method ran faster than SVD with an embedding and extraction time of 0.6308 and 0.2163 seconds against 0.8419 and 0.2935 seconds. The proposed method successfully reduced the running time while maintaining imperceptibility and robustness.
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References
Adi, P.W., Ramhanti, F.Z. & Winarno, E., Robust Watermarking through Dual Band IWT and Chinese Remainder Theorem, Bulletin Electr. Eng. Informatics, 7(4), pp. 561-569, 2018.
Singh, S.P. & Bhatnagar, G., A New Robust Watermarking System in Integer DCT Domain, J. Vis. Commun. Image Represent, 53, pp. 86-101, 2018.
Roy, S. & Pal, A.K., A Blind DCT Based Color Watermarking Algorithm for Embedding Multiple Watermarks, AEU - Int. J. Electron. Commun., 72, pp. 149-161, 2017.
Sangeetha, N. & Anita, X., Entropy Based Texture Watermarking Using Discrete Wavelet Transform, Optik (Stuttgart), 160, pp. 380-388, 2018.
Gangadhar, Y., Giridhar Akula, V.S. & Reddy, P.C., An Evolutionary Programming Approach for Securing Medical Images Using Watermarking Scheme in Invariant Discrete Wavelet Transformation, Biomed. Signal Process. Control, 43, pp. 31-40, 2018.
Najih, A., Al-Haddad, S.A.R., Ramli, A.R., Hashim, S.J. & Nematollahi, M.A., Digital Image Watermarking Based on Angle Quantization in Discrete Contourlet Transform, J. King Saud Univ. - Comput. Inf. Sci., 29(3), pp. 288-294, 2017.
Etemad, S. & Amirmazlaghani, M., A New Multiplicative Watermark Detector in the Contourlet Domain Using T Location-Scale Distribution, Pattern Recognit., 77, pp. 99-112, 2018.
Patra, J.C., Karthik, A. & Bornand, C., A Novel CRT-Based Watermarking Technique for Authentication of Multimedia Contents, Digit. Signal Process, 20(2), pp. 442-453, 2010.
Adi, P.W., Astuti, Y.P. & Subhiyakto, E.R., Imperceptible Image Watermarking based on Chinese Remainder Theorem over the Edges, in 4th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI ), pp. 1-5, 2017.
Lin, P.Y., Imperceptible Visible Watermarking Based on Postcamera Histogram Operation, J. Syst. Softw., 95, pp. 194-208, 2014.
Manikandan, V.M. & Masilamani, V., Histogram Shifting-Based Blind Watermarking Scheme for Copyright Protection in 5G, Comput. Electr. Eng., 72, pp. 614-630, 2018.
Jia, S.L., A Novel Blind Color Images Watermarking Based on SVD, Optik (Stuttgart), 125(12), pp. 2868-2874, 2014.
Araghi, T.K., Manaf, A.A. & Araghi, S.K., A Secure Blind Discrete Wavelet Transform Based Watermarking Scheme Using Two-Level Singular Value Decomposition, Expert Syst. Appl., 112, pp. 208-228, 2018.
Mohan, B.C. & Kumar, S.S., A Robust Image Watermarking Scheme using Singular Value Decomposition, J. Multimed., 3(1), pp. 7-15, 2008.
Adi, P.W. & Rahmanti, F. Z., Robust Integer Haar Wavelet Based Watermarking using Singular Value Decomposition, J. Ilmu Komput. dan Inf., 9(1), pp. 26-34, 2016.
lvarez, V., Armario, J.A., Falcon, R.M., Frau, M.D., Gudiel, F., G1/4emes, M.B. & Osuna, A., Generating Binary Partial Hadamard Matrices, Discret. Appl. Math., 263, pp. 2-7, 2019.
Yue, J., Han, J., Li, L. & fa Bai, L., Denoising Analysis of Spatial Pixel Multiplex Coded Spectrometer with Hadamard H-Matrix, Opt. Commun., 407, pp. 355-360, 2018.
Wang, Z., Bovik, A.C., Sheikh, H.R. & Simoncelli, E.P., Image Image Quality Assessment: From Error Visibility to Structural Similarity, IEEE Trans. Image Process., 13(4), pp. 600-612, 2004.
