Abstract
The various kinds of unauthorized use and modification of data has been constantly increasing day by day and very common due to the enormous growth of multimedia information on the Internet. Thus, authenticity of the data is one of the major issues in the defence data transmission as well as in secured transmission. To overcome this sort of problem, digital watermarking is supposed to be one of the legitimate solutions as it provides possible validation, safe, and secure transmission of secret data. Here, a robust and secure digital image watermarking method for the protection of copyright has been developed which involves LWT in combination with SVD. The latest approach to wavelet transform is LWT while the significant transform technique is SVD and the obtained experimental results are cross-validated by using inverse LWT and SVD. In order to create and insert a digital signature, the signature mechanism has been used after embedding the watermark and the ownership is authenticated before extracting watermarks in this research work. The robustness of the proposed method for several common image processing attacks like Mean, Median, Gaussian, Shear, Rotation, and Crop is checked by computing the two significant performance metrics, namely, PSNR and MSE. Here, the similarity is also checked by determining the NCC values. Finally, the watermarking scheme suggested in this work is compared with various existing research works which show that the algorithm used in the proposed scheme works fairly in terms of PSNR, MSE, and NCC.
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References
V. Sthul, N.N. Khalsa, Digital watermarking of an image using wavelet transform. Int. J. Pure Appl. Res. Eng. Technol. (lJPRET) 1(8), 365–378 (2013)
K.S. Rawat, S. Goyal, R. Gupta, Discrete wavelet based image watermarking: an idea leads to security. J. Biom. 1(1), 06–10 (2010)
H. Yang, Y. Liang, X. Wang et al., A DWT- based evaluation method of imperceptibility of watermark in watermarked color image, in International Conference on Wavelet Analysis and Pattern Recognition, vol. 1 (2007), pp. 198–203
Iffat Rehman Ansari, Shahnawaz Uddin, Signal denoising using discrete wavelet transform. Int. J. Eng. Technol. Sci. Res. (IJETSR) 3(11), 23–31 (2016)
J. Kaur, N. Singh, C. Jain, An improved image watermarking technique implementing 2-DWT and SVD, in IEEE International Conference on Recent Trends in Electronics Information Communication Technology (2016), pp. 1855–1859
M. Radouane, R. Messoussi, R. Touahni, T. Boujiha, Robust method of digital image watermarking using SVD transform on DWT coefficients with optimal block, in International Conference on Multimedia Computing and Systems (ICMCS) (2014)
N. Shrinivas, N. Naveena, K. Manikantan, Robust digital image watermarking using dwt + svd approach, in IEEE International Conference on Computational Intelligence and Computing Research (2015)
T. Bhuyan, V. Srivastava, F. Thakkar, Shuffled SVD based robust and secure digital image watermarking, in International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT) (2016)
K.R. Sheth, V.V. Nath, Secured digital image watermarking with discrete cosine transform and discrete wavelet transform method, in International Conference on Advances in Computing, Communication and Automation (ICACCA) (Spring, Berlin, 2016)
T. Pardhu, B.R. Perli, Digital image watermarking in frequency domain, in International Conference on Communication and Signal Processing (2016)
A. Furqan, M. Kumar, Study and analysis of robust DWT-SVD domain based digital image watermarking technique using MATLAB, in IEEE International Conference on Computational Intelligence and Communication Technology (2015)
N.M. Makbol, B.E. Khoo, Robust blind image watermarking scheme based on redundant discrete wavelet transform and singular value decomposition. AEU–Int. J. Electron. Commun. 67(2), 102–112 (2013)
Y. Dejun, Y. Rijing, L. Hongyan, Z. Jiangchao, A digital watermarking scheme based on singular value decomposition and discrete wavelet transform, in International Conference on Computer Science and Network Technology (2011)
V. Santhi, A. Thangavelu, DWT-SVD combined full band robust watermarking technique for color images in YUV color space. Int. J. Comput. Theory Eng. 1(4), 424–429 (2009)
H. Tao, L. Chongmin, J.M. Zain, A.N. Abdalla, Robust image watermarking theories and techniques; a review. J. Appl. Res. Technol. (2014)
W. Sweldens, The lifting scheme: a construction of second generation wavelets. SIAM J. Math. Anal. 29(2), 511–546 (1998)
A. Manjunath, Comparison of discrete wavelet transform (DWT), lifting wavelet transform (LWT), stationary wavelet transform (SWT) and S-transform in power quality analysis. Eur. J. Sci. Res. 39(4), 569–576 (2010)
H. Kiya, M. Iwahashi, O. Watanabe, A new class of lifting wavelet transform for guaranteeing losslessness of specific signals, in IEEE International Conference on Acoustics, Speech and Signal Processing (2008), pp. 3273–3276
S.K. Jinna, L. Ganesan, Lossless image watermarking using lifting wavelet transform. Int. J. Recent Trends Eng. 2(1), 191–195 (2009)
K. Loukhaoukha, Optimal image watermarking algorithm based on LWT-SVD via multi-objective ant colony optimization. J. Inform. Hiding Multimed. Signal Process. 2(4), 303–319 (2011)
K. Loukhaoukha, J. Chouinard, Hybrid watermarking algorithm based on SVD and lifting wavelet transform for ownership verification, in 11th Canadian Workshop on Information Theory (2009), pp. 177–182
H. Zhang, C. Wang, X. Zhou, A robust image watermarking scheme based on SVD in the spatial domain. Future Internet 9(3), 45 (2017)
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Naaz, S., Sana, E., Ansari, I.R. (2020). Comparative Analysis of Digital Image Watermarking Based on Lifting Wavelet Transform and Singular Value Decomposition. In: Jain, L., Virvou, M., Piuri, V., Balas, V. (eds) Advances in Bioinformatics, Multimedia, and Electronics Circuits and Signals. Advances in Intelligent Systems and Computing, vol 1064. Springer, Singapore. https://doi.org/10.1007/978-981-15-0339-9_7
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