基于几何不变性的鲁棒图像水印方法
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摘要
当今，数字图像作为人类获取和交换信息的主要媒体，以其直观、生动和跨语言等优势，广泛地应用于人类生产生活的各个方面。随着人类活动范围的不断扩大，数字图像的应用领域也将随之不断深化。然而，飞速发展的信息技术使得数字图像的信息安全面临严峻挑战。针对这一问题，数字水印技术作为一门新兴的交叉学科应运而生，并且在近二十年里得到了快速发展。由于水印图像在传输过程中会遭受无意或恶意的攻击，这一问题已经成为数字水印技术走向成功应用的重要瓶颈。因此，研究鲁棒的数字图像水印技术成为近年来多媒体内容信息安全领域的热点问题之一。
本文针对鲁棒图像水印方法所面临的挑战性问题，分别从几何失真校正、水印嵌入与检测模型及水印系统安全性等方面研究了基于几何不变性的鲁棒图像水印的解决之道。本文的主要工作可概括如下：
(1)提出了一种基于SIFT特征点匹配的图像校正方法。首先通过对原始图像和失真图像的SIFT特征点进行匹配，计算图像几何失真参数；然后对失真图像进行逆变换恢复其内容，实现了几何攻击下失真水印图像的几何校正。
(2)针对基于特征匹配校正方法仅能处理如旋转、缩放等有限几何攻击类型的问题，运用RANSAC优化迭代算法设计了一种新的图像失真校正方法。在特征点匹配之后，进一步滤除误匹配的特征点对，通过逐步迭代获得精确的几何变换模型，从而对失真图像进行精确校正，不仅提高了图像恢复质量而且扩展了图像几何校正的适应范围。
(3)鉴于实际应用环境中几何攻击对水印图像的降质影响，将稳定的图像特征与变换域嵌入策略相结合，提出了一种基于特征匹配的Curvelet域抗几何攻击图像水印方法。首先利用特征点匹配对失真图像进行校正，以恢复水印与图像内容的同步性，然后针对校正后的水印图像，以Curvelet系数为载体，实施水印嵌入和检测，不仅增强了水印的鲁棒性而且扩大了水印的嵌入容量。
(4)为了进一步提高水印方法抵抗几何攻击的鲁棒性，提出了一种基于迭代校正的Zernike矩鲁棒图像水印方法。首先利用基于图论的分割算法和特征区域选择策略构建稳定独立的特征区域，并借助Zernike矩实现水印的嵌入和检测；随后通过RANSAC迭代算法优化水印图像的几何校正模型，使嵌入的水印具有良好的不可感知性与鲁棒性。
(5)为了进一步增强水印系统的安全性，结合可逆元胞自动机提出了基于元胞自动机的鲁棒水印多重加密方法。首先将水印图像转换成二值序列，然后采用不同的可逆元胞自动机规则分别对辅助信息、水印与水印图像进行级联式加密，最终得到加密水印图像，有效解决了鲁棒图像水印方法存在的安全问题。
综上所述，本文将模式分类、计算机视觉等领域的基本理论引入到鲁棒数字图像水印的框架中，所提出的五种数字图像水印新方法从不同角度有效解决了现有方法存在的问题，为实现数字图像版权保护与内容认证提供了新途径，为鲁棒水印算法的设计提供了新思路。
Recently, digital images serve as a key media for information acquisition andtransmission and are therefore widely used in different fields due to some characteristics,such as direct viewing, vividness and cross-language. However, the fast development ofthe information technology has brought to forefront security concerns with the use ofdigital images. To solve the above problem, the digital watermarking technique has beenproposed and rapidly developed in the past twenty years. Usually, stego imagesinevitably suffer from the common image processing operations and geometric attacksduring the transmission, which is an important bottleneck to their usage in practicalapplications. Therefore, robust watermarking techniques for digital images haveattracted increasing attention for copyright protection in multimedia informationsecurity.
To target the challenging problems of the robust image watermarking, this thesismakes an extensive study of robust image watermark based on geometry invariancefrom such aspects as geometry rectification, watermark embedding and detection modeland security analysis of watermark system. The main contents of this paper aresummarized as follows.
(1) An image rectification method based on SIFT feature points matching isproposed. Firstly, the geometric distortion parameters of stego images are computed bymatching SIFT feature points from original images and stego versions. Following this,the invert transform is employed to restore image content. Based on these properties, theproposed method can accomplish geometry rectification for distorted stego images.
(2) Since the rectification method based on feature matching can only handlelimited kinds of geometric attacks such as rotation and scaling transformations, a novelrectification method using RANSAC iteration algorithm is designed in this thesis.Following the feature matching process, the feature point pairs matched wrongly arefurther removed and the geometric transform model can be accurately determined byiteration procedure. In this way, the distorted images can be restored, which not onlyenhances the image quality but also improves the adaptibiliby of image geometricrectification.
(3) By considering the effects of geometric attacks on stego images in practicalapplications, an image watermarking method based on feature matching in the Curvelet domain is proposed against geometric attacks, which combines the stable image featuresand embedding strategy in transform domain. The distorted image is firstly restoredusing feature matching in order to resynchronize the watermarks and images.Watermarks are embedded into the restored stego images by modifying Curveletcoefficients, which leads to an improvement of robustness and capacity of watermarks.
(4) To further enhance the robustness against geometric attacks, an imagewatermarking method based on iteration optimization and Zernike moment is proposed.Firstly, both the graph-based segmentation algorithm and selection strategy of featureregions are used to obtain the stable and non-overlapping feature regions. Then, thewatermark embedding and detection algorithm based on the Zernike moment isdesigned. Finally, the geometry rectification model is optimized by the RANSACiteration algorithm, which is helpful for the improvement of imperceptibility androbustness of watermarks.
(5) To further improve the security of the watermarking system, a multipleencryption algorithm based on cellular automata (CA) for robust watermarking isproposed. Firstly, the watermarked image is converted into binary sequences. Secondly,different CAs rules are used for encryption of side information, watermarks and stegoimages. Finally, the encrypted stego images can be obtained. The proposed methodeffectively solves the security problem of the watermarking system.
Generally, we integrate the basic theories of pattern classification and computervision into robust image watermarking mechanism and propose five novel methods indifferent aspects. The proposed methods can overcome the drawbacks of the existingmethods and provide new ways for copyright protection and content authentication ofdigital images.
本文针对鲁棒图像水印方法所面临的挑战性问题，分别从几何失真校正、水印嵌入与检测模型及水印系统安全性等方面研究了基于几何不变性的鲁棒图像水印的解决之道。本文的主要工作可概括如下：
(1)提出了一种基于SIFT特征点匹配的图像校正方法。首先通过对原始图像和失真图像的SIFT特征点进行匹配，计算图像几何失真参数；然后对失真图像进行逆变换恢复其内容，实现了几何攻击下失真水印图像的几何校正。
(2)针对基于特征匹配校正方法仅能处理如旋转、缩放等有限几何攻击类型的问题，运用RANSAC优化迭代算法设计了一种新的图像失真校正方法。在特征点匹配之后，进一步滤除误匹配的特征点对，通过逐步迭代获得精确的几何变换模型，从而对失真图像进行精确校正，不仅提高了图像恢复质量而且扩展了图像几何校正的适应范围。
(3)鉴于实际应用环境中几何攻击对水印图像的降质影响，将稳定的图像特征与变换域嵌入策略相结合，提出了一种基于特征匹配的Curvelet域抗几何攻击图像水印方法。首先利用特征点匹配对失真图像进行校正，以恢复水印与图像内容的同步性，然后针对校正后的水印图像，以Curvelet系数为载体，实施水印嵌入和检测，不仅增强了水印的鲁棒性而且扩大了水印的嵌入容量。
(4)为了进一步提高水印方法抵抗几何攻击的鲁棒性，提出了一种基于迭代校正的Zernike矩鲁棒图像水印方法。首先利用基于图论的分割算法和特征区域选择策略构建稳定独立的特征区域，并借助Zernike矩实现水印的嵌入和检测；随后通过RANSAC迭代算法优化水印图像的几何校正模型，使嵌入的水印具有良好的不可感知性与鲁棒性。
(5)为了进一步增强水印系统的安全性，结合可逆元胞自动机提出了基于元胞自动机的鲁棒水印多重加密方法。首先将水印图像转换成二值序列，然后采用不同的可逆元胞自动机规则分别对辅助信息、水印与水印图像进行级联式加密，最终得到加密水印图像，有效解决了鲁棒图像水印方法存在的安全问题。
综上所述，本文将模式分类、计算机视觉等领域的基本理论引入到鲁棒数字图像水印的框架中，所提出的五种数字图像水印新方法从不同角度有效解决了现有方法存在的问题，为实现数字图像版权保护与内容认证提供了新途径，为鲁棒水印算法的设计提供了新思路。
Recently, digital images serve as a key media for information acquisition andtransmission and are therefore widely used in different fields due to some characteristics,such as direct viewing, vividness and cross-language. However, the fast development ofthe information technology has brought to forefront security concerns with the use ofdigital images. To solve the above problem, the digital watermarking technique has beenproposed and rapidly developed in the past twenty years. Usually, stego imagesinevitably suffer from the common image processing operations and geometric attacksduring the transmission, which is an important bottleneck to their usage in practicalapplications. Therefore, robust watermarking techniques for digital images haveattracted increasing attention for copyright protection in multimedia informationsecurity.
To target the challenging problems of the robust image watermarking, this thesismakes an extensive study of robust image watermark based on geometry invariancefrom such aspects as geometry rectification, watermark embedding and detection modeland security analysis of watermark system. The main contents of this paper aresummarized as follows.
(1) An image rectification method based on SIFT feature points matching isproposed. Firstly, the geometric distortion parameters of stego images are computed bymatching SIFT feature points from original images and stego versions. Following this,the invert transform is employed to restore image content. Based on these properties, theproposed method can accomplish geometry rectification for distorted stego images.
(2) Since the rectification method based on feature matching can only handlelimited kinds of geometric attacks such as rotation and scaling transformations, a novelrectification method using RANSAC iteration algorithm is designed in this thesis.Following the feature matching process, the feature point pairs matched wrongly arefurther removed and the geometric transform model can be accurately determined byiteration procedure. In this way, the distorted images can be restored, which not onlyenhances the image quality but also improves the adaptibiliby of image geometricrectification.
(3) By considering the effects of geometric attacks on stego images in practicalapplications, an image watermarking method based on feature matching in the Curvelet domain is proposed against geometric attacks, which combines the stable image featuresand embedding strategy in transform domain. The distorted image is firstly restoredusing feature matching in order to resynchronize the watermarks and images.Watermarks are embedded into the restored stego images by modifying Curveletcoefficients, which leads to an improvement of robustness and capacity of watermarks.
(4) To further enhance the robustness against geometric attacks, an imagewatermarking method based on iteration optimization and Zernike moment is proposed.Firstly, both the graph-based segmentation algorithm and selection strategy of featureregions are used to obtain the stable and non-overlapping feature regions. Then, thewatermark embedding and detection algorithm based on the Zernike moment isdesigned. Finally, the geometry rectification model is optimized by the RANSACiteration algorithm, which is helpful for the improvement of imperceptibility androbustness of watermarks.
(5) To further improve the security of the watermarking system, a multipleencryption algorithm based on cellular automata (CA) for robust watermarking isproposed. Firstly, the watermarked image is converted into binary sequences. Secondly,different CAs rules are used for encryption of side information, watermarks and stegoimages. Finally, the encrypted stego images can be obtained. The proposed methodeffectively solves the security problem of the watermarking system.
Generally, we integrate the basic theories of pattern classification and computervision into robust image watermarking mechanism and propose five novel methods indifferent aspects. The proposed methods can overcome the drawbacks of the existingmethods and provide new ways for copyright protection and content authentication ofdigital images.
引文
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[1]焦李成,侯彪,王爽,刘芳著.图像多尺度几何分析理论与应用.西安电子科技大学出版社,2008.
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[7] Simitopoulos D., Koutsonanos D., and Strintzis M. Robust image watermarking based ongeneralized radon transformations. IEEE Trans. Circ. Syst. Video Tech.,13(8):732-745,2003.
[8] Lin C., Wu M., Bloom J., Cox I., Miller M., and Lui Y. Rotation, scale and translationresilient watermarking for images. IEEE Trans. Image Process.,10(5):767-782,2001.
[9] Jayalakshmi M., Merchant S., and Desai U. Digital watermarking in contourlet domain. Proc.IEEE Int. Conf. Pattern Recognition,2006:861-864.
[10] Campisi P., Kundur D., and Neri A. Robust digital watermarking in the ridgelet domain. IEEESignal Process. Lett.,11(10):826-830,2004.
[11] Tao P., Dexter S., and Eskicioglu A. Robust digital image watermarking in curvelet domain.Proc. SPIE,6819:68191B–68191B-12,2008.
[12] Bas P., Chassery J. M., and Macq B. Geometrically invariant watermarking using featurepoints. IEEE Trans. Image Process.,11(9):1014-1028,2002.
[13] Lee H., Kim H., and Lee H. Robust image watermarking using local invariant features. Opt.Eng.,45(3)1-11,2006.
[14] Seo J. and Yoo C. Image watermarking based on invariant regions of scale-spacerepresentation. IEEE Trans. Signal Process.,54(4):1537-1549,2006.
[15] Gao X., Deng C., Li X., and Tao D. Geometric distortion insensitive image watermarking inaffine covariant regions. IEEE Trans. Syst. Man Cybern. C Appl. Rev.,40(3):278-286,2010.
[16] Candes E., Demanet L., and Donoho D. Fast discrete curvelet transform. Available:www.curvelet.org
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