Raheleh MOVAGHAR KHORSAND, Hossein BIZAKI KHALEGHI

A new approach for digital image watermarking to predict optimal blocks using artificial neural networks

In this paper, we propose a novel nonblind digital image watermarking based on discrete wavelet transform and singular value decomposition. This robust scheme takes advantage of artificial neural networks for selecting suitable image blocks in which the watermark signal can be embedded. Local characteristics of the blocks such as luminance and texture sensitivity are the main criteria that the selections are based on. Generally, selection is based on a prediction of the results with the objective of transparency and watermark resilience. In other words, before embedding the water mark signal, it is estimated which blocks would be the best for embedding the signals to achieve the desired robustness and quality. Simulation results confirm the superiority of the proposed scheme in terms of the transparency of the images as well as robustness under various kinds of attacks.

PDF

___

[1] Abdullatif M, Zeki AM, Chebil J, Gunawan TS. Properties of digital image watermarking. In: IEEE 2013 Signal Processing and Its Applications, 9th International Colloquium; 810 March 2013; Kuala Lumpur, Malaysia. New York, NY, USA: IEEE. pp. 235-240.
[2] Elba¸sı E. Robust multimedia watermarking. Hidden Markov model approach for video sequences. Turk J Elec Eng & Comp Sci 2010; 18: 159-170.
[3] Singh YS, Devi BP, Singh KM. A review of different techniques on digital image watermarking scheme. Int J Eng Res 2013; 2: 193-199.
[4] Li J, Wu F. Robust watermarking for text images based on Arnold scrambling and DWT-DFT. In: Proceedings of the 2013 Mechatronic Sciences Electric Engineering and Computer International Conference; 2022 December 2013; Shengyang, China. New York, NY, USA: IEEE. pp. 1182-1186.
[5] Arya RK, Singh S, Saharan R. A secure non-blind block based digital image watermarking technique using DWT and DCT. In: IEEE 2015 Advances in Computing, Communications and Informatics International Conference; 1013 August 2015; Kochi, India. New York, NY, USA: IEEE. pp. 2042-2048.
[6] Song C, Xiao P, Sudirman S, Merabti M. Region adaptive digital image watermarking system using DWT-SVD algorithm. In: NASA/ESA 2014 Adaptive Hardware and Systems Conference; 1417 July 2014; Leicester, UK. New York, NY, USA: IEEE. pp. 196-201.
[7] Nguyen TH, Duong DM, Duong DA. Robust and high capacity watermarking for image based on DWT-SVD. In: IEEE RIVF 2015 Computing & Communication Technologies-Research, Innovation and Vision for Future International Conference; 2528 January 2015; Can Tho, Vietnam. New York, NY, USA: IEEE. pp. 83-88.
[8] Lagzian S, Soryani M, Fathy M. A new robust watermarking scheme based on RDWT-SVD. Int J Intell Inform Process 2011; 2: 27-35.
[9] Jane O, Elba¸sı E. A new approach of nonblind watermarking methods based on DWT and SVD via LU decomposition. Turk J Elec Eng & Comp Sci 2014; 22: 1354-1366.
[10] Qi H, Zheng D, Zhao J. Human visual system based adaptive digital image watermarking. Signal Process 2008; 88: 174-188.
[11] Radouane M, Boujiha T, Messoussi R, Touahni R. A robust method for digital image watermarking based on combination of SVD, DWT and DCT using optimal block. J Theor Appl Inform Technol 2014; 59: 297-303.
[12] Jin C, Wang S. Applications of a neural network to estimate watermark embedding strength. In: WIAMIS 2007 Image Analysis for Multimedia Interactive Services Eighth International Workshop; 68 June 2007; Santorini, Greece. New York, NY, USA: IEEE. p. 68.
[13] Lou DC, Liu JL, Hu MC. Adaptive digital watermarking using neural network technique. In: IEEE 2003 Security Technology Proceedings of the 37th Annual International Carnahan Conference; 1416 October 2003; Taipei, Taiwan. New York, NY, USA: IEEE. pp. 325-332.
[14] Huang S, Zhang W, Feng W, Yang H. Blind watermarking scheme based on neural network. In: WCICA 2008 Intelligent Control and Automation Proceedings of the 7th World Congress; 2527 June 2008; Chongqing, China. New York, NY, USA: IEEE. pp. 5985-5989.
[15] Aslantas V. A singular-value decomposition-based image watermarking using genetic algorithm. Int J Elec Commun 2008; 62: 386-394.
[16] Ramanjaneyulu K, Rajarajeswari K. Wavelet-based oblivious image watermarking scheme using genetic algorithm. IET Image Process 2012; 6: 364-373.
[17] Jagadeesh B, Kumar SS, Rajeswari KR. A genetic algorithm based oblivious image watermarking scheme using singular value decomposition (SVD). In: NETCOM 2009 Networks & Communications First International Conference; 2729 December 2009; Chennai, India. New York, NY, USA: IEEE. pp. 224-229.
[18] Yalman Y, Ert¨urk ˙I. A new color image quality measure based on YUV transformation and PSNR for human vision system. Turk J Elec Eng & Comp Sci 2013; 21: 603-612.