An SVD-based image watermarking in wavelet domain using SVR and PSO |
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| Authors: | Hung-Hsu Tsai Yu-Jie Jhuang Yen-Shou Lai |
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| Affiliation: | 1. Department of Information Management, National Formosa University, Huwei, Yulin 632, Taiwan;2. Shin-Guang Elementary School, Yulin 646, Taiwan;1. Department of Electrical Engineering, K. N. Toosi University of Technology, Tehran, Iran;2. Department of Computer Engineering and Information Technology, Amirkabir university of Technology, Tehran, Iran;1. School of Information Science and Technology, Sun Yat-Sen University, Guangzhou 510006, PR China;2. School of Information Management, Sun Yat-Sen University, Guangzhou 510006, PR China;3. Shenzhen Key Laboratory of Media Security, College of Information Engineering, Shenzhen University, Shenzhen 518060, PR China;1. Department of Biomedical Engineering, School of Medicine, Shenzhen University, National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Nanhai Ave 3688, Shenzhen, Guangdong 518060, China;2. School of Electrical and Electronic Engineering, Nanyang Technological University, 639798, Singapore;3. College of Computer Science and Technology, Shenzhen University, Nanhai Ave 3688, Shenzhen, Guangdong 518060, China;1. School of Information Science and Engineering, Lu Dong University, Yantai 264025, PR China;2. Key Laboratory of Advanced Control and Optimization for Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai 200237, PR China;1. Department of Computer Science, University of Delhi, Delhi, India;2. Department of Electronics, Deendayal Upadhyay College, University of Delhi, Delhi, India;3. Department of Computer Science, Deendayal Upadhyay College, University of Delhi, Delhi, India |
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| Abstract: | The paper presents a novel blind watermarking scheme for image copyright protection, which is developed in the discrete wavelet transform (DWT) and is based on the singular value decomposition (SVD) and the support vector regression (SVR). Its embedding algorithm hides a watermark bit in the low–low (LL) subband of a target non-overlap block of the host image by modifying a coefficient of U component on SVD version of the block. A blind watermark-extraction is designed using a trained SVR to estimate original coefficients. Subsequently, the watermark bit can be computed using the watermarked coefficient and its corresponding estimate coefficient. Additionally, the particle swarm optimization (PSO) is further utilized to optimize the proposed scheme. Experimental results show the proposed scheme possesses significant improvements in both transparency and robustness, and is superior to existing methods under consideration here. |
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