IJCA – Robust Digital Image Watermarking Scheme in Discrete Wavelet Transform domain using Support Vector Machines

B Jagadeesh, Rajesh P Kumar and Chenna P Reddy. Article: Robust Digital Image Watermarking Scheme in Discrete Wavelet Transform domain using Support Vector Machines. International Journal of Computer Applications 73(14):1-7, July 2013. Full text available. BibTeX Novel Application of Multi-Layer Perceptrons (MLP) Neural Networks to Model HIV in South Africa using Seroprevalence Data from Antenatal Clinics B Jagadeesh, Rajesh P Kumar and Chenna P Reddy. Article: Robust Digital Image Watermarking Scheme in Discrete Wavelet Transform domain using Support Vector Machines. @article{key:article, author = {B. Jagadeesh and P. Rajesh Kumar and P. Chenna Reddy}, title = {Article: Robust Digital Image Watermarking Scheme in Discrete Wavelet Transform domain using Support Vector Machines}, journal = {International Journal of Computer Applications}, year = {2013}, volume = {73}, number = {14}, pages = {1-7}, month = {July}, note = {Full text available} } This paper presents a robust and blind watermarking scheme for copyright protection of images in discrete wavelet transform domain based on the support vector machines (SVMs). This scheme is based on the relation between the coefficients in various sub bands in discrete wavelet transform decomposition. The proposed scheme is very secured and robust to various attacks, viz. , Low pass Filtering, Salt & Pepper noise, Gamma Correction, JPEG Compression, Row-Column Copying, Row-column blanking, Bit plane removal, Cropping, Resize and Histogram Equalization etc. Experimental results show that the proposed scheme has significant improvements in both robustness and imperceptibility and superior to an algorithm proposed by Li et al. in terms of Normalized Cross correlation (NC) and Peak Signal to Noise Ratio (PSNR). Steve R Gunn, 1998, 'Support vector machines forclassification and regression', Technical Report, ISIS Department of electronics and computer science, University of Southampton. Wu. Jianzhen, 2009, 'A RST invariant watermarking scheme utilizing support vector machine and image moments for synchronization', Fifth International Conference on Information Assurance and Security, China, pp. 572–574. Xiang-Yang Wang, Zi-Han Xu, Hong-Ying Yang, 2009, 'A robust image watermarking algorithm using SVM detection', Expert Sys. Appl. 36 (5), pp. 9056–9064. H. H. Tsai, D. W. Sun, 2007, 'Color image watermark extraction based on support vector machines', Inform. Sci. 177 (2), pp. 550–569. P. H. H. Then, and Y. C. Wang, 2005, 'Perceiving Digital Watermark Detection as Image Classification Problem using Support Vector Machine', Proc. of CITA05, pp. 198-206. P. H. H. Then, and Y. C. Wang, 2006, 'Support Vector Machine as Digital Watermark Detector,' In Proceedings of SPIE-IS&T Electronic Imaging, SPIE. Fu, Y. , Shen, R. , Lu, H. , 2004, 'Optimal watermark Detection based on support vector machines', Proceedings of the International Symposium on Neural Networks, Dalian, China, pp. 552–557. H. H. Tsaia, H. C. Tsenga, Y. S. Laib, 2010, 'Robust lossless image watermarking based on ?-trimmed mean algorithm and support vector machine', J. Sys. Software. 83 (6), pp. 1015 –1028. Chun-hua Li, Ling He-fei, Lu Zheng-ding, 2007, 'Semi-fragile watermarking based on SVM for image authentication', IEEE International Conference on Multimedia and Expo, Beijing, China, pp. 1255–1258. Hong Peng, Jun Wang, Weixing Wang, 2010, 'Image watermarking method in multiwavelet Domain based on support vector machine', J. Sys. Software, 83 (8) pp. 1470 –1477. Source.


Яндекс.Метрика Рейтинг@Mail.ru Free Web Counter
page counter
Last Modified: April 18, 2016 @ 7:12 am