| Digital Watermarking Algorithm Based on Wavelet Transform and Neural Network |
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| 作者姓名： | WANG Zhenfei ZHAI Guangqun WANG Nengchao |
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| 作者单位： | [1]College of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China [2]College of Information Engineering, Zhengzhou University, Zhengzhou 450001, Henan, China |
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| 摘 要： | An effective blind digital watermarking algorithm based on neural networks in the wavelet domain is presented. Firstly, the host image is decomposed through wavelet transform. The significant coefficients of wavelet are selected according to the human visual system （HVS） characteristics. Watermark bits are added to them. And then effectively cooperates neural networks to learn the characteristics of the embedded watermark related to them. Because of the learning and adaptive capabilities of neural networks, the trained neural networks almost exactly recover the watermark from the watermarked image. Experimental results and comparisons with other techniques prove the effectiveness of the new algorithm.
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| 关 键 词： | 数字水印 神经网络 小波变换 人的视觉系统 |
| 文章编号： | 1007-1202（2006）06-1667-04 |
| 收稿时间： | 2006-05-20 |
Digital watermarking algorithm based on wavelet transform and neural network |
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| WANG Zhenfei ZHAI Guangqun WANG Nengchao.Digital Watermarking Algorithm Based on Wavelet Transform and Neural Network[J].Wuhan University Journal of Natural Sciences,2006,11(6):1667-1670. |
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| Authors: | Wang Zhenfei Zhai Guangqun Wang Nengchao |
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| Institution: | (1) College of Computer Science and Technology, Huazhong University of Science and Technology, 430074 Wuhan, Hubei, China;(2) College of Information Engineering, Zhengzhou University, 450001 Zhengzhou, Henan, China |
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| Abstract: | An effective blind digital watermarking algorithm based on neural networks in the wavelet domain is presented. Firstly, the host image is decomposed through wavelet transform. The significant coefficients of wavelet are selected according to the human visual system (HVS) characteristics. Watermark bits are added to them. And then effectively cooperates neural networks to learn the characteristics of the embedded watermark related to them. Because of the learning and adaptive capabilities of neural networks, the trained neural networks almost exactly recover the watermark from the watermarked image. Experimental results and comparisons with other techniques prove the effectiveness of the new algorithm. |
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| Keywords: | digital watermarking neural networks wavelet transform human visual system |
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