基于混沌和图像矩的鲁棒零水印技术研究
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摘要
由于零水印采取零嵌入的方式,并未修改原始数字媒体,因而数字媒体的视觉质量和完整性等得到了保证,也不存在嵌入式水印中的鲁棒性与不可见性的矛盾。尽管前对零水印安全技术的研究取得了一定的进展,但已有的零水印方案对几何攻击的抵抗能力很差。因此,开展具有高鲁棒性的零水印技术研究非常必要。
围绕这一主题,本文首先分类并全面综述了水印技术研究现状,接着介绍了混沌和图像矩技术,然后将混沌和图像矩技术应用于抗攻击的鲁棒零水印技术研究中,在复合混沌构造、笛卡儿坐标矩和极坐标矩的应用、多倍零水印以及图像篡改定位等方面进行深入研究。本文主要工作及贡献包括：
(1)利用定义在笛卡儿坐标空间的Tchebichef不变矩和经过复合混沌优化后的SVR,提出一种抗几何攻击零水印方案。为了改善数字水印抵抗几何攻击的性能,基于定义在笛卡儿坐标空间的Tchebichef不变矩和优化的回归型支持向量机(Support Vector for Regression, SVR)提出一种鲁棒零水印方案。该方案定义了一种复合混沌系统,并给出了该复合混沌系统的密钥空间、随机复杂度及抗预测能力分析。把该复合混沌系统应用于水印的加密,提高了零水印方案的安全性。同时,利用该复合混沌系统给出了改进的变尺度混沌优化SVR方法。对非线性Hermite函数进行的函数逼近测试结果表明在采用复合混沌对SVR优化后,各项性能测试指标都得到了改善。将检测图像的受攻击样本与水印图像的Tchebichef不变矩通过优化的SVR进行关联和训练,构造SVR MIMO系统模型用于零水印的检测。仿真结果和性能分析表明,提出的零水印方案具有较好的抗几何攻击能力,综合性能优于其它同类算法。
(2)提出了一种基于定义在极坐标空间上的Bessel-Fourier矩特征向量的鲁棒可视零水印算法
定义在笛卡儿坐标空间上的离散正交矩,其几何变换不变性较难获取。而定义在极坐标空间Bessel-Fourier矩是最新提出的一种正交矩,它具备良好的旋转不变性且易获得,同时比其他同类正交矩性能更优越。因而本文基于Bessel-Fourier矩特征向量提出了一种鲁棒可视零水印算法。首先,对图像进行平移、缩放规范化处理,然后计算规范化图像的Bessel-Fourier矩幅度,得到的幅度值具有旋转不变性,将其二值化后构造成特征图像,并与logo图像作异或操作后生成校验图像,将校验图像保存在可信机构(Trusted Authority, TA)。在对检测图像进行版权认证时,将提取的特征图像与校验图像作异或操作后同原始logo图像做比较,从视觉上就可判断检测图像有无版权,同时也可以客观指标准确率AR (Accuracy Rate)来衡量。
(3)设计了基于曲率特征域的多倍零水印版权认证方案
基于曲率特征域,提出了一种多倍零水印版权认证方案。该方案设计一种图像增强和噪声抑制方法并应用于曲率多特征的提取,利用Bessel-fourier矩相位分量提出一种受攻击图像旋转角度的简单估计算法,并采用具有强泛化能力和快速学习特点的极限学习机(Extreme Learning Machine, ELM)训练模型来完成对多倍零水印的检测。利用提出方案对Lena图像、卡通图像、医疗图像、遥感图像和艺术图像等类型图像进行了测试,试验结果表明提出的无损版权认证方案比现有的四种方法具有更好的整体性能,尤其在抗大尺度剪切和大角度旋转攻击方面。最后,对影响算法性能的几个因素分别作出了定性和定量的分析,这些因素包括相位及幅度分量、特征向量维度和ELM优化。
(4)提出了一种基于混沌映射的图像认证和篡改定位零水印方法
基于混沌映射提出了一种零水印图像认证方案,实现在同时遭受信号处理和篡改攻击时,能正确提取水印信息,而且能检测被篡改区域的准确位置和具体形状。Arnold映射良好的置乱性能、Rossler耦合混沌的大密钥空间及对初值的极端敏感性增强了零水印的安全性和鲁棒性。仿真和理论分析表明提出的方案比现有的图像认证和篡改定位水印方案具有更优的性能。
Because zero-watermarking scheme does not change the content of original digital media at the same time of protecting image copyright, hence, the visual quality and integrity of original digital media are assured and the contradiction between robustness and invisibility does not exist. In spite that the research of zero-watermarking makes certain progress, but the current zero-watermarking schemes have poor ability against geometrical attacks. Therefore, it is very necessary to undertake the research on zero-watermarking technology with strong robustness.
This dissertation provides a comprehensive overview of the watermarking technology. Also, chaos and image moment are briefly introduced. Afterwards, the dissertation applies chaos and image moment to robust zero-watermarking research, which focuses on the construction of composite chaos, the application of image moments defined in Cartesian coordinate and polar coordinate, multiple zero-watermarking and tamper localization of image. The main contents and contributions are as follows.
(1) A zero-bit watermarking algorithm resisting to geometrical attacks is proposed using Tchebichef moment invariants and the optimized support vector for regression.
The problem to improve the performance of resisting geometric attacks in digital watermarking is addressed in this dissertation. Based on Tchebichef moment invariants defined in the Cartesian coordinate and the optimized support vector for regression (SVR), a zero-bit watermarking algorithm is presented. The scheme develops a kind of composite chaos and gives the analysis of key space, randomicity and complexity, and the ability against prediction for composite chaos. The watermarking image is encrypted with composite chaos which can strengthen the safety of the proposed algorithm. Meanwhile, an improved mutative scale chaos optimization algorithm for SVR is presented utilizing composite chaos. The nonlinear Hermite function is adopted for the function approximating test, and the test results indicate each performance index is improved using the optimized SVR. Finally, the SVR MIMO training model is constructed for the detection of zero-watermarking using the relationship between Tchebichef moment invariants of detected image and watermarking characteristics. Performance analysis and simulations demonstrate that the proposed algorithm possesses better security and stronger robustness than some similar methods.
(2) Based on Bessel-Fourier moment feature vector, a robust visible zero-watermarking algorithm is presented.
The geometrical invariability of the discrete orthogonal moments defined in the Cartesian coordinate is difficult to obtain. Bessel-Fourier moment defined in the polar coordinate, as a new image moment, has a good rotation invariability which can be easily gained, and has better performance than other similar orthogonal moments. Therefore, this dissertation presents a robust visible zero-watermarking algorithm based on Bessel-Fourier moment feature vector. First, image normalization is used for the invariance of translation and scaling. Then the magnitudes of Bessel-Fourier moments of normalized image are computed, which have rotation invariance and are used to construct the feature image. Finally, the verification image is generated by performing XOR operation between the feature image and logo image, which is then saved into TA (trusted authority). When the detected image is tested, XOR operation between the verification image and the extracted feature image from the detected image is performed, then the result of XOR operation is compared with the logo image, and the copyright property of the detected image can be deduced by vision on the comparison result, which can also be measured by the object index of AR (Accuracy Rate).
(3) A multiple zero-watermarking scheme is designed in curvature-feature domain.
The scheme designs a multiple zero-watermarking algorithm based on Bessel-Fourier moment and extreme learning machine (ELM) in curvature-feature domain, develops a method for strengthening of feature and depressing of noise influence in curvature-feature domain, presents a simple estimation algorithm of the rotation angle for the rotation-attacked image using Bessel-Fourier moment phase component, and adopts ELM model with strong generalization ability and fast learning speed to complete the detection for the multiple zero-watermarking. The experimental results, including five types of images, indicate the proposed lossless copyright authentication scheme has better overall performance compared to other four current methods, especially in the aspect of resisting high ratio cropping and large angle rotation attacks. Finally, both quantitative and qualitative analysis for some factors affecting the algorithm performance are given, and these factors include phase and magnitude components, feature vector dimension and ELM optimization.
(4) A chaos mapping-based zero-watermarking scheme for image authentication and tamper localization is developed.
Based on chaos mapping, an image authentication scheme with zero-watermarking is proposed. The main advantage of the proposed scheme not only can extract correctly the watermarking under common signal processing and tamper attack, but also can detect the precise location and concrete shape of the tampered region. The good scrambling performance of Arnold cat mapping, large key space and extreme sensibility to initial value of Rossler coupling chaos can strengthen the safety and robustness of zero-watermarking. Simulation and theoretical analysis indicate the proposed scheme has better performance than the existing watermarking algorithms for image authentication and tamper localization.
围绕这一主题,本文首先分类并全面综述了水印技术研究现状,接着介绍了混沌和图像矩技术,然后将混沌和图像矩技术应用于抗攻击的鲁棒零水印技术研究中,在复合混沌构造、笛卡儿坐标矩和极坐标矩的应用、多倍零水印以及图像篡改定位等方面进行深入研究。本文主要工作及贡献包括：
(1)利用定义在笛卡儿坐标空间的Tchebichef不变矩和经过复合混沌优化后的SVR,提出一种抗几何攻击零水印方案。为了改善数字水印抵抗几何攻击的性能,基于定义在笛卡儿坐标空间的Tchebichef不变矩和优化的回归型支持向量机(Support Vector for Regression, SVR)提出一种鲁棒零水印方案。该方案定义了一种复合混沌系统,并给出了该复合混沌系统的密钥空间、随机复杂度及抗预测能力分析。把该复合混沌系统应用于水印的加密,提高了零水印方案的安全性。同时,利用该复合混沌系统给出了改进的变尺度混沌优化SVR方法。对非线性Hermite函数进行的函数逼近测试结果表明在采用复合混沌对SVR优化后,各项性能测试指标都得到了改善。将检测图像的受攻击样本与水印图像的Tchebichef不变矩通过优化的SVR进行关联和训练,构造SVR MIMO系统模型用于零水印的检测。仿真结果和性能分析表明,提出的零水印方案具有较好的抗几何攻击能力,综合性能优于其它同类算法。
(2)提出了一种基于定义在极坐标空间上的Bessel-Fourier矩特征向量的鲁棒可视零水印算法
定义在笛卡儿坐标空间上的离散正交矩,其几何变换不变性较难获取。而定义在极坐标空间Bessel-Fourier矩是最新提出的一种正交矩,它具备良好的旋转不变性且易获得,同时比其他同类正交矩性能更优越。因而本文基于Bessel-Fourier矩特征向量提出了一种鲁棒可视零水印算法。首先,对图像进行平移、缩放规范化处理,然后计算规范化图像的Bessel-Fourier矩幅度,得到的幅度值具有旋转不变性,将其二值化后构造成特征图像,并与logo图像作异或操作后生成校验图像,将校验图像保存在可信机构(Trusted Authority, TA)。在对检测图像进行版权认证时,将提取的特征图像与校验图像作异或操作后同原始logo图像做比较,从视觉上就可判断检测图像有无版权,同时也可以客观指标准确率AR (Accuracy Rate)来衡量。
(3)设计了基于曲率特征域的多倍零水印版权认证方案
基于曲率特征域,提出了一种多倍零水印版权认证方案。该方案设计一种图像增强和噪声抑制方法并应用于曲率多特征的提取,利用Bessel-fourier矩相位分量提出一种受攻击图像旋转角度的简单估计算法,并采用具有强泛化能力和快速学习特点的极限学习机(Extreme Learning Machine, ELM)训练模型来完成对多倍零水印的检测。利用提出方案对Lena图像、卡通图像、医疗图像、遥感图像和艺术图像等类型图像进行了测试,试验结果表明提出的无损版权认证方案比现有的四种方法具有更好的整体性能,尤其在抗大尺度剪切和大角度旋转攻击方面。最后,对影响算法性能的几个因素分别作出了定性和定量的分析,这些因素包括相位及幅度分量、特征向量维度和ELM优化。
(4)提出了一种基于混沌映射的图像认证和篡改定位零水印方法
基于混沌映射提出了一种零水印图像认证方案,实现在同时遭受信号处理和篡改攻击时,能正确提取水印信息,而且能检测被篡改区域的准确位置和具体形状。Arnold映射良好的置乱性能、Rossler耦合混沌的大密钥空间及对初值的极端敏感性增强了零水印的安全性和鲁棒性。仿真和理论分析表明提出的方案比现有的图像认证和篡改定位水印方案具有更优的性能。
Because zero-watermarking scheme does not change the content of original digital media at the same time of protecting image copyright, hence, the visual quality and integrity of original digital media are assured and the contradiction between robustness and invisibility does not exist. In spite that the research of zero-watermarking makes certain progress, but the current zero-watermarking schemes have poor ability against geometrical attacks. Therefore, it is very necessary to undertake the research on zero-watermarking technology with strong robustness.
This dissertation provides a comprehensive overview of the watermarking technology. Also, chaos and image moment are briefly introduced. Afterwards, the dissertation applies chaos and image moment to robust zero-watermarking research, which focuses on the construction of composite chaos, the application of image moments defined in Cartesian coordinate and polar coordinate, multiple zero-watermarking and tamper localization of image. The main contents and contributions are as follows.
(1) A zero-bit watermarking algorithm resisting to geometrical attacks is proposed using Tchebichef moment invariants and the optimized support vector for regression.
The problem to improve the performance of resisting geometric attacks in digital watermarking is addressed in this dissertation. Based on Tchebichef moment invariants defined in the Cartesian coordinate and the optimized support vector for regression (SVR), a zero-bit watermarking algorithm is presented. The scheme develops a kind of composite chaos and gives the analysis of key space, randomicity and complexity, and the ability against prediction for composite chaos. The watermarking image is encrypted with composite chaos which can strengthen the safety of the proposed algorithm. Meanwhile, an improved mutative scale chaos optimization algorithm for SVR is presented utilizing composite chaos. The nonlinear Hermite function is adopted for the function approximating test, and the test results indicate each performance index is improved using the optimized SVR. Finally, the SVR MIMO training model is constructed for the detection of zero-watermarking using the relationship between Tchebichef moment invariants of detected image and watermarking characteristics. Performance analysis and simulations demonstrate that the proposed algorithm possesses better security and stronger robustness than some similar methods.
(2) Based on Bessel-Fourier moment feature vector, a robust visible zero-watermarking algorithm is presented.
The geometrical invariability of the discrete orthogonal moments defined in the Cartesian coordinate is difficult to obtain. Bessel-Fourier moment defined in the polar coordinate, as a new image moment, has a good rotation invariability which can be easily gained, and has better performance than other similar orthogonal moments. Therefore, this dissertation presents a robust visible zero-watermarking algorithm based on Bessel-Fourier moment feature vector. First, image normalization is used for the invariance of translation and scaling. Then the magnitudes of Bessel-Fourier moments of normalized image are computed, which have rotation invariance and are used to construct the feature image. Finally, the verification image is generated by performing XOR operation between the feature image and logo image, which is then saved into TA (trusted authority). When the detected image is tested, XOR operation between the verification image and the extracted feature image from the detected image is performed, then the result of XOR operation is compared with the logo image, and the copyright property of the detected image can be deduced by vision on the comparison result, which can also be measured by the object index of AR (Accuracy Rate).
(3) A multiple zero-watermarking scheme is designed in curvature-feature domain.
The scheme designs a multiple zero-watermarking algorithm based on Bessel-Fourier moment and extreme learning machine (ELM) in curvature-feature domain, develops a method for strengthening of feature and depressing of noise influence in curvature-feature domain, presents a simple estimation algorithm of the rotation angle for the rotation-attacked image using Bessel-Fourier moment phase component, and adopts ELM model with strong generalization ability and fast learning speed to complete the detection for the multiple zero-watermarking. The experimental results, including five types of images, indicate the proposed lossless copyright authentication scheme has better overall performance compared to other four current methods, especially in the aspect of resisting high ratio cropping and large angle rotation attacks. Finally, both quantitative and qualitative analysis for some factors affecting the algorithm performance are given, and these factors include phase and magnitude components, feature vector dimension and ELM optimization.
(4) A chaos mapping-based zero-watermarking scheme for image authentication and tamper localization is developed.
Based on chaos mapping, an image authentication scheme with zero-watermarking is proposed. The main advantage of the proposed scheme not only can extract correctly the watermarking under common signal processing and tamper attack, but also can detect the precise location and concrete shape of the tampered region. The good scrambling performance of Arnold cat mapping, large key space and extreme sensibility to initial value of Rossler coupling chaos can strengthen the safety and robustness of zero-watermarking. Simulation and theoretical analysis indicate the proposed scheme has better performance than the existing watermarking algorithms for image authentication and tamper localization.
引文
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