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Reseach Article

A Hybrid Video Watermarking Technique based on DWT, SVD and SCHUR Decomposition

by Ananya Adhikari, Mihir Sing
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 179 - Number 9
Year of Publication: 2018
Authors: Ananya Adhikari, Mihir Sing
10.5120/ijca2018916079

Ananya Adhikari, Mihir Sing . A Hybrid Video Watermarking Technique based on DWT, SVD and SCHUR Decomposition. International Journal of Computer Applications. 179, 9 ( Jan 2018), 15-23. DOI=10.5120/ijca2018916079

@article{ 10.5120/ijca2018916079,
author = { Ananya Adhikari, Mihir Sing },
title = { A Hybrid Video Watermarking Technique based on DWT, SVD and SCHUR Decomposition },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2018 },
volume = { 179 },
number = { 9 },
month = { Jan },
year = { 2018 },
issn = { 0975-8887 },
pages = { 15-23 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume179/number9/28828-2018916079/ },
doi = { 10.5120/ijca2018916079 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:54:52.906566+05:30
%A Ananya Adhikari
%A Mihir Sing
%T A Hybrid Video Watermarking Technique based on DWT, SVD and SCHUR Decomposition
%J International Journal of Computer Applications
%@ 0975-8887
%V 179
%N 9
%P 15-23
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Video watermarking is a technique that used to protect the multimedia data, video in reference to authentication, proof of ownership, copy control etc. In this paper a robust video watermarking scheme is proposed that will protect videos from being unauthorized manipulation by the intruder. A hybrid transform technique consists of Discrete Wavelet Transform (DWT), Schur decomposition, Singular Value Decomposition (SVD) and a visual attention region determination scheme is used to determine the region of interest and region of non interest blocks of video frames. To make the scheme robust, watermark is embedded in the region of non interest blocks of HL band of the frame. The robustness against various attacks has been compared with high Normalized Cross Correlation (NCC) values and the imperceptibility of the watermarked image with the original cover image has been compared with indicated high achievable Peak Signal to Noise Ratio (PSNR) values. The experimental results show that the proposed method has achieved a satisfactory performance against various notable attacks.

References
  1. Ling H., Wang L., Zou F., Lu Z., Li P., “Robust video watermarking based on affine invariant regions in the compressed domain”, Signal Processing 91, 1863–1875, 2011.
  2. Preda R., Vizireanu D.N., “Robust wavelet-based video watermarking scheme for copyright protection using the human visual system”, Journal of Electronic Imaging 20, 013022-1–013022-8, 2012.
  3. Kirthika A., Senthilkumar A. and Nithya T., “DWT Based Watermarking System for Video Authentication Using Region of Interest”, Middle-East Journal of Scientific Research 166-170, 2016.
  4. Dixit Akanksha, Sharma Pankaj, Kulshreshtha Vyom, “Blind Video Watermarking based on DWTSHUR and Optimized Firefly Algorithm”, International Journal of Computer Applications (0975 – 8887), Volume 147 – No.1, August 2016.
  5. Lama Rajab, Tahani Al-Khatib, Ali Al-Haj, “A Blind DWT-SCHUR Based Digital Video Watermarking Technique”, Journal of Software Engineering and Applications, 8, 224-233, 2015.
  6. Antonio Cedillo-Hernandez , Manuel Cedillo-Hernandez , Mireya Garcia-Vazquez , Mariko Nakano Miyatake , Hector Perez-Meana , Alejandro Ramirez-Acosta, “Transcoding resilient video watermarking scheme based on spatio-temporal HVS and DCT”, Signal Processing 97, 40-54, Elsevier, 2014
  7. Agilandeeswari L. & Ganesan K., “A robust color video watermarking scheme based on hybrid embedding techniques”, Multimed Tools Appl, 75:8745–8780, 2016.
  8. Agilandeeswari L., Ganesan K, “An Efficient Hilbert And Integer Wavelet Transform Based Video Watermarking”, Journal of Engineering Science and Technology Vol. 11, No. 3, 327 – 345, 2016
  9. Nasrin M. Makbol, Bee Ee Khoo, “A new robust and secure digital image watermarking scheme based on the integer wavelet transform and singular value decomposition”, Digital Signal Processing, Elsevier, 2014.
  10. Xia, X.G., Boncelet, C.G. and Arce, G.R., “A Multiresolution Watermark for Digital Images Proceedings”, International Conference on Image Processing, Santa Barbara, 548-551, 26-29 October 1997.
  11. Chunlin Song , Sud Sudirman, Madjid Merabti, “A robust region-adaptive dual image watermarking technique”, Journal of Visual communication and image reconstruction, Elsevier, pp. 549–568, Feb. 2012.
  12. Joseph Anumol, Anusudha K., “Robust watermarking based on DWT SVD”, International Journal of Signal & Image Processing, Issue. 1, Vol. 1, October 2013
  13. Hamidreza Sadreazami, Marzieh Amini, “Highly Robust Image Watermarking in Contourlet Domain Using Singular Value Decomposition”, 2012.
  14. Lijie Cao, “Singular Value Decomposition Applied To Digital Image Processing”, Division of Computing Studies, Arizona State University Polytechnic Campus, Mesa, Arizona State University polytechnic Campus, 2006.
  15. Kang-Ting Hu, Jin-Jang Leou, and Han-Hui Hsiao, “Visual Attention Region Determination for H.264 Videos”, International Conference on Pattern Recognition, November 11-15, 2012.
  16. Chandra Mohan B. and Veera Swamy K., " On the use of Schur Decomposition for Copyright Protection of Digital Images", International Journal of Computer and Electrical Engineering, Vol. 2, No. 4, pp. 1793-8163, August, 2010.
  17. Thomos N, Boulgouris NV, Strintzis MG, “Optimized transmission of JPEG 2000 streams over wireless channels”, IEEE Trans Image Process 5(1):54–67,2006.
Index Terms

Computer Science
Information Sciences

Keywords

Discrete wavelet Transform (DWT) Schur Decomposition Singular Value Decomposition (SVD) Visual Attention Region.