| Robust Image Watermarking Using Local Invariant Features and Independent Component Analysis |
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| 作者姓名： | ZHANG Hanling LIU Jie |
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| 作者单位： | College of Computer and Communication, Hunan University, Changsha 410082, Hunan, China |
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| 摘 要： | This paper proposes a novel robust image watermarking scheme for digital images using local invariant features and Independent Component Analysis （ICA）. Most present watermarking algorithms are unable to resist geometric distortions that desynchronize the location. The method we propose here is robust to geometric attacks. In order to resist geometric distortions, we use a local invariant feature of the image called the scale invariant feature transform, which is invariant to translation and scaling distortions. The watermark is inserted into the circular patches generated by scale-invariant key point extractor. Rotation invariance is achieved using the translation property of the polar-mapped circular patches. Our method belongs to the blind watermark category, because we use Independent Component Analysis for detection that does not need the original image during detection. Experimental results show that our method is robust against geometric distortion attacks as well as signal-processing attacks.
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| 关 键 词： | 数字水印 几何失真 水印同步 局部不变特征 |
| 文章编号： | 1007-1202（2006）06-1930-04 |
| 收稿时间： | 2006-01-20 |
Robust image watermarking using local invariant features and independent component analysis |
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| ZHANG Hanling LIU Jie.Robust Image Watermarking Using Local Invariant Features and Independent Component Analysis[J].Wuhan University Journal of Natural Sciences,2006,11(6):1931-1934. |
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| Authors: | Zhang Hanling Liu Jie |
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| Institution: | (1) College of Computer and Communication, Hunan University, 410082 Changsha, Hunan, China |
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| Abstract: | This paper proposes a novel robust image watermarking scheme for digital images using local invariant features and Independent Component Analysis(ICA). Most present watermarking algorithms are unable to resist geometric distortions that desynchronize the location. The method we propose here is robust to geometric attacks. In order to resist geometric distortions, we use a local invariant feature of the image called the scale invariant feature transform, which is invariant to translation and scaling distortions. The watermark is inserted into the circular patches generated by scale-invariant key point extractor. Rotation invariance is achieved using the translation property of the polar-mapped circular patches. Our method belongs to the blind watermark category, because we use Independent Component Analysis for detection that does not need the original image during detection. Experimental results show that our method is robust against geometric distortion attacks as well as signal-processing attacks. |
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| Keywords: | robust watermarking geometrical attack watermark synchronization local invariant features |
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