Singular Values Decomposition and Lifting Wavelet Transform for Speech Signal Embedding into Digital Image

Author(s): Mourad Talbi*, Med Salim Bouhlel.

Journal Name: Recent Advances in Electrical & Electronic Engineering
Formerly Recent Patents on Electrical & Electronic Engineering

Volume 12 , Issue 2 , 2019

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Graphical Abstract:


Abstract:

Background: In this paper, we propose a secure image watermarking technique which is applied to grayscale and color images. It consists in applying the SVD (Singular Value Decomposition) in the Lifting Wavelet Transform domain for embedding a speech image (the watermark) into the host image.

Methods: It also uses signature in the embedding and extraction steps. Its performance is justified by the computation of PSNR (Pick Signal to Noise Ratio), SSIM (Structural Similarity), SNR (Signal to Noise Ratio), SegSNR (Segmental SNR) and PESQ (Perceptual Evaluation Speech Quality).

Results: The PSNR and SSIM are used for evaluating the perceptual quality of the watermarked image compared to the original image. The SNR, SegSNR and PESQ are used for evaluating the perceptual quality of the reconstructed or extracted speech signal compared to the original speech signal.

Conclusion: The Results obtained from computation of PSNR, SSIM, SNR, SegSNR and PESQ show the performance of the proposed technique.

Keywords: Speech image, color image, grayscale image, singular values decomposition, lifting wavelet transform, image watermarking, watermark, secure.

[1]
R. Sun, H. Sun, and T. Yao, "A SVD and quantization based semifragile watermarking technique for image authentication In", 6th International Conference on Signal Processing. Beijing, China, pp. 1592-1595, 2002
[2]
C.C. Chang, P.Y. Tsai, and M.H. Lin, "SVD-based digital image watermarking scheme", Pattern Recognit. Lett., vol. 26, pp. 1577-1586, 2005.
[3]
J.M. Shieh, D.C. Lou, and M.C. Chang, "A semi-blind digital watermarking scheme based on singular value decomposition", Comput. Stand. Interfaces, vol. 28, pp. 428-440, 2006.
[4]
R. Liu, and T. Tan, "An SVD-based watermarking scheme for protecting rightful ownership", IEEE Trans. Multimed., vol. 4, pp. 121-128, 2002.
[5]
M. Naor, and A. Shamir, "Visual cryptography”, Adv. Cryptology- Eurocrypt, In:", Workshop on the Theory and Application of Cryptographic Techniques. Perugia, Italy, pp. 1-12, 1995
[6]
S. Kamble, V. Maheshkar, S. Agarwal, and V.K. Srivastava, "DWT-SVD based secured image watermarking for copyright protection using visual cryptography", Comput. Sci. Inf. Technol., pp. 143-150, 2012.
[7]
C-C. Chang, J-C. Chuang, and P-Yu. Lin, "Sharing a secret two-tone image in two gray-level images", Proceedings of the 11th International Conference on Parallel and Distributed Systems, ICPADS’05. Fukuoka, Japan, 2005
[8]
R. Wang, Q. Cheng, and T.S. Huang, "Identify region of interest for video watermark embedment with principle component analysis on multiple cues In:", Proceedings of the eighth ACM international conference on Multimedia. California, USA, pp. 459-461, 2000
[9]
Q. Cheng, and T.S. Huang, "A framework for blind digital video watermarking with dual watermarks", Int. Conf. Vis. Commun. Image Process.. 2002
[10]
A.K. Gupta, and M.S. Raval, "A robust and secure watermarking scheme based on singular values replacement", Sadhana, vol. 37, pp. 425-440, 2012.
[11]
I. Daubeches, and W. Sweldens, "Factoring wavelet transform into lifting steps", J. Fourier Anal. Appl., vol. 4, pp. 247-269, 1998.
[12]
W. Fan, J. Chen, and J. Zhen, SPIHT algorithm based on fast lifting wavelet transform in image compressionY. Hao (Eds.): CIS Part II, LNAI 3802, pp. 838-844, 2005
[13]
B. Lei, I.Y. Soon, F. Zhou, Z. Li, and H. Lei, "A robust audio watermarking scheme based on lifting wavelet transform and singular value decomposition", Signal Processing, vol. 92, pp. 1985-2001, 2012.
[14]
K. Ourkhaoukha, J.Y. Chouinard, and M.H. Taieb, "Multi-objective genetic algorithm optimization for image watermarking based on singular value decomposition and Lifting wavelet transform", Lect. Notes Comput. Sci., vol. 6134, pp. 394-403, 2010.
[15]
V.S. Verma, and R.K. Jha, "Improved watermarking technique based on significant difference of lifting wavelet coefficients", Signal Image Video Process., vol. 9, pp. 1443-1450, 2015.
[16]
"R. Mehta1, N. Rajpal1 and V.P. Vishwakarma, ‘‘LWT-QR decomposition based robust and efficient image watermarking scheme using Lagrangian SVR", Multimedia Tools Appl., vol. 75, pp. 4129-4150, 2016.
[17]
A. Joseph, and K. Anusudha, "Robust watermarking based on DWT SVD", Internat. J. Sig. Image Process.,. Vol. 1, 2013
[18]
P.M. Naini, "Digital Watermarking Using MATLAB", Eng. Educat.Res. MATLAB. Dr. Ali Assi (Ed.), ISBN: 978-953-307-656-0, InTech, Available from: http://www.intechopen.com/books/ engineering-education-and-research-using-matlab/digital-watermarking-using-matlab
[19]
http://www.ias.ac.in/sadhana/Pdf2012Aug/425.pdf, https://www. mathworks.com/matlabcentral/fileexchange/41686-dwt-svd-robust-and-securewatermarking-scheme Vol. 37, Part 4, August 2012, pp. 425-440. Indian Academy of Sciences
[20]
https://www.mathworks.com/matlabcentral/fileexchange/64554-svd-domain watermarking?requestedDomain=true
[21]
S. Lagzian, M. Soryani, and M. Fathy, "A new robust watermarking scheme based on RDWT-SVD", Internat. J. Intell. Inform.Process. Vol. 2, 2011
[22]
M. Talbi, and B.F. Sira, "Speech modulation for image watermarking", Internat. J. Multimed. Image Process. Vol. 6, 2016
[23]
M. Talbi, "Speech enhancement based on stationary bionic wavelet transform and maximum a posterior estimator of magnitude-squared spectrum", Int. J. Speech Technol., vol. 20, pp. 75-88, 2017.


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Article Details

VOLUME: 12
ISSUE: 2
Year: 2019
Page: [138 - 151]
Pages: 14
DOI: 10.2174/2352096511666180511151646
Price: $58

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