基于图像特征点的数字水印算法

几何攻击作用在加载有水印的图像上,水印同步信息被破坏,导致水印检测失败。为了恢复已失去的同步信息,提出一种基于筛选尺度不变特征估计几何攻击参数的数字水印算法。首先提取图像的尺度不变特征,利用像素差的平方和筛选尺度不变特征,去除易受几何攻击影响的尺度不变特征,保证最小二乘法迭代运算快速收敛,迭代一次就能得到基本准确的几何变换参量;水印信息进行游程编码,在其码值对应的载体图像的DCT块内嵌入。实验结果表明,该算法能获得很好的图像质量,且能十分有效地抵抗各种几何攻击。     

基于SIFT特征点的抗几何攻击水印算法

提出一种利用尺度不变特征变换（SIFT）特征点实现对抗几何攻击的水印方案。基于特征点构造Delavnay三角网,依靠SIFT特征点的抗几何变换性实现图像三角形区域的抗几何攻击。在提取部分图像内容的基础上,按照多对一的原则,使用改进的加性方法嵌入水印信息。实验表明,该算法能够较好地抵抗几何攻击和一般的信号处理攻击。     

基于Contourlet域特征点的抗几何攻击水印方法

有效抵抗几何攻击的水印算法是目前水印技术研究的难点之一,很小的几何变形就可能使大多数水印算法失效.对图像Contourlet变换和Harris-Affine算子的特性进行了分析和讨论,在此基础上提出了一种以仿射不变特征点的基于Contourlet的抗几何攻击水印算法.首先,用Contourlet变换提取出多尺度、多方向的纹理信息;再用Harris-Affine检测算子从变换域的中、低频方向子带中提取出仿射不变特征点,结合自适应局部结构的特征尺度确定特征区域,并用U变换对其归一化处理,水印就自适应地嵌入到归一化后的区域中;水印嵌入采纳矢量量化的策略,将水印信息重复嵌入到不同方向子带、多个不相交的局部仿射不变特征区域.检测时,利用特征点实现水印的重同步,采用多数原则来提取水印的位信息,无需求助于原始图像.仿真结果表明,算法不仅具有较好的透明性,而且对常规信号处理和去仿射攻击均具有较好的鲁棒性     

抗几何失真的局部数字水印算法

抗几何攻击一直是数字水印中的难点问题,为了更好地解决这个问题,基于图像的几何不变域,提出了一种抗几何失真的局部数字水印算法.算法利用显著性检测器检测到的具有平移、缩放和旋转不变性特性的圆形显著区域来嵌入水印.如何利用显著区域构造不变区域以获得平移、缩放及旋转不变性,以及如何从不变区域中筛选出适合嵌水印的区域,为要解决的重点问题,首先将水印进行几何变换来匹配各个水印嵌入区域的形状,再不可感知地嵌入到各个水印嵌入区域中.还着重讨论了如何利用显著区域获得平移、缩放及旋转不变性.实验表明该算法能很好地抵抗一般的信号处理攻击及旋转、缩放、裁剪和线性变换等几何攻击.     

一种新的空域抗几何攻击图像水印算法

提出了一种基于特征与量化的空域抗几何攻击图像水印算法---FAQ算法. 采取的主要方法有: 1)利用图像中的局部最稳定特征点生成具有几何不变性的圆形特征区域, 用于水印的同步; 2)将特征区域分解为具有旋转不变性的扇形区域, 并在空域利用奇偶量化嵌入水印; 3)设计了一种奇偶检测器盲提取水印. 实验结果表明FAQ算法能获得很高的图像质量, 且能有效地抵抗常规信号处理攻击、旋转/缩放/平移(Rotation/scaling/translation, RST)攻击及其组合攻击.     

基于SIFT和非采样Contourlet变换的鲁棒水印算法

针对常见抗几何攻击水印算法存在的不足,设计一种基于SIFT和非采样Contourlet(NSCT)变换的鲁棒水印算法。算法首先利用尺度不变特征变换在载体图像的尺度空间上提取特征点并形成矩形特征区域,然后水印信息自适应量化嵌入特征区域的NSCT低频变换系数中,最后保存若干个稳定特征点用于几何校正。实验结果表明,该算法不仅具有很好的透明性,同时对常见图像处理攻击和几何攻击均具有很强的鲁棒性。     

基于特征点模板的Contourlet域抗几何攻击水印算法研究

抵抗几何攻击的数字水印是目前水印算法研究的热点与难点之一,一个微弱不可察觉的几何攻击就可能使绝大多数水印算法失效.文中对图像的Contourlet变换特性进行了分析和讨论,在此基础上提出了一种以特征点为模板的基于Contourlet的抗几何攻击水印算法,包括:(1)在Contourlet变换域最高阶方向子带的相同带内坐标中搜索纹理最丰富的位置作为嵌入位置,这样水印在被嵌入到图像重要区域的同时也保证其被嵌到纹理丰富的区域中;(2)根据嵌入点在低频对应位置的能量和高尺度同方向子带对应位置的纹理信息,确定了一种自适应的水印嵌入强度的策略,使得水印在嵌入位置和嵌入强度的选择上都保证了嵌入的水印具有很好的透明性和极大的鲁棒性;(3)改进了Harris-Laplace算子,利用该算子从含有水印的图像中提取出具有几何形变鲁棒性的特征点作为模板;(4)水印检测时,先利用特征点模板对应点之间的变换关系实现水印重同步,然后通过统计图像的相关性来验证水印的存在.仿真实验表明,所提出的水印算法不仅具有很好的透明性,而且对常见的图像处理和几何攻击具有很好的鲁棒性.     

基于LFRs的大容量抗几何攻击水印算法*

如何有效抵抗几何攻击是目前水印技术研究的难点之一,且已有抗几何攻击水印算法的嵌入容量有限。提出了一种利用尺度不变特征变换（SIFT）特征点确定的局部特征区域（LFRs）嵌入水印的大容量抗几何攻击的水印算法。算法首先从图像的非抽样的Contourlet域（NSCT）低频分量中提取出SIFT中等尺度的稳定特征点,并通过最小生成树聚类算法的选择策略获得一组分布均匀且彼此独立的圆形特征区域;然后对每个圆形区域进行等角度的扇形分割和等面积的同心圆环分割,划分成等面积的子块;最后采用奇偶量化将经过混沌加密的水印嵌入到     

一种基于角点检测的鲁棒数字图像水印算法

几何攻击是数字图像水印领域中一个富有挑战性的问题。提出一种以图像角点为特征点,基于奇偶量化嵌入/检测的空间域局部化鲁棒数字图像水印算法。采取的主要方法有:(1)采用带有自适应阈值和动态支持区域的基于曲率尺度空间的角点检测算法进行鲁棒角点检测;(2)基于图像纹理复杂度进行角点筛选,并以筛选后的角点为圆心形成具有几何不变性的圆形特征区域,用于水印的重同步;(3)在特征区域设计一种圆环形的水印模式,并在空间域采用经典的奇偶量化方法嵌入并检测水印。实验表明,该算法在嵌入水印后仍能保持较高的图像视觉质量,对常规信号处理和包括旋转、缩放、平移、剪切及其组合在内的几何攻击均具有较强的鲁棒性。     

基于二代Bandelet变换与稳定特征检测的鲁棒图像水印算法

当前基于特征点的图像水印技术主要是将水印信息隐藏到采用固定值构建的特征不变区域中,其抵御几何变换能力不佳。对此,设计二代Bandelet变换耦合稳定特征检测的图像水印算法。引入尺度不变特征变换方法,提取载体图像中潜在的特征点;根据特征点的Hessian矩阵对应的特征值,构建不稳定特征点消除规则;根据特征点的尺度因子,计算圆形半径,建立局部特征不变区域;定义鲁棒特征区域选择机制,找出合适的水印嵌入位置;引入二代Bandelet变换,处理鲁棒特征区域,获取并选择出重要的Bandelet系数;设计水印嵌入方法,将经过仿射映射加密后的二值水印隐藏到重要的Bandelet系数,获取水印图像;检测水印图像的稳定特征点,联合二代Bandelet变换,从水印图像中复原二值水印。测试结果显示:与已有的鲁棒水印方案相比,该方案具有更高的不可感知性与鲁棒性,其输出的水印图像对应的差分图更为理想,在多种几何攻击下的复原水印失真度最小。     

Invariant image watermarking using multi-scale Harris detector and wavelet moments

Desynchronization attack is known as one of the most difficult attacks to resist, which can desynchronize the location of the watermark and hence causes incorrect watermark detection. It is a challenging work to design a robust image watermarking scheme against desynchronization attacks. Based on multi-scale Harris detector and wavelet moment theory, we propose a new content based image watermarking algorithm with low computational complexity, good visual quality and reasonable resistance toward desynchronization attacks in this paper. Firstly, the steady image feature points are extracted from the origin host by using multi-scale Harris detector, and the local feature regions (LFRs) are constructed adaptively according to the feature scale theory. Then, the LFRs are image normalized, and significant regions are obtained from the normalized LFRs by utilizing the invariant centroid theory. Finally, the digital watermark is embedded into the LFRs by modifying wavelet moment invariants of the significant regions. By binding the watermark with the geometrically invariant image features, the watermark detection can be done without synchronization error. Experimental results show that the proposed image watermarking is not only invisible and robust against common image processing operations as sharpening, noise adding, and JPEG compression etc, but also robust against the desynchronization attacks such as rotation, translation, scaling, row or column removal, cropping, and local random bend etc.     

Robust localized image watermarking based on invariant regions

The robustness of the localized watermarking methods mainly depends on the robustness of the feature locating the watermark. Based on the mean luminance of the disk, a rotation and scale invariant feature extraction algorithm is proposed. A theoretical verification of the rotation and scale invariance of extracted feature points in the continuous image is further performed. The extracted feature points are used to construct rotation and scale invariant circular regions, where the watermark is embedded after affine normalization. Experimental results show that the constructed regions fit the watermarking applications much better than those in previous feature-based watermarking schemes from the aspect of robustness against common attacks including filtering, JPEG compression, cropping, rotation and scaling, and the proposed localized image watermarking scheme has better robustness than previous feature-based watermarking schemes against common signal process and geometrical attacks while maintaining imperceptibility.     

A robust content based image watermarking using local invariant histogram

Desynchronization attack is known as one of the most difficult attacks to resist, which can desynchronize the location of the watermark and hence causes incorrect watermark detection. Based on multi-scale SIFT (Scale Invariant Feature Transform) detector and local image histogram shape invariance, we propose a new content based image watermarking algorithm with good visual quality and reasonable resistance toward desynchronization attacks in this paper. Firstly, the stable image feature points are extracted from the original host by using multi-scale SIFT detector, and the local feature regions (LFRs) are constructed adaptively according to the feature scale theory. Then, the discrete Fourier transform (DFT) is performed on the LFR, and the local image histogram is extracted from a selected DFT amplitude range. Finally, the bins of the histogram are divided into many groups, and the digital watermark is embedded into LFR by reassigning the number of DFT amplitudes in bin groups. By binding the watermark with the geometrically invariant image features, the watermark detection can be done without synchronization error. Experimental results show that the proposed image watermarking is not only invisible and robust against common image processing operations such as sharpening, noise adding, and JPEG compression, but also robust against the desynchronization attacks such as rotation, translation, scaling, row or column removal, and cropping.     

A robust color image watermarking using local invariant significant bitplane histogram

Desynchronization attacks that cause displacement between embedding and detection are usually difficult for watermark to survive. It is a challenging work to design a robust image watermarking scheme against desynchronization attacks, especially for color images. In this paper, we propose a robust color image watermarking approach based on local invariant significant bitplane histogram. The novelty of the proposed approach includes: 1) A fast and effective color image feature points detector is constructed, in which probability density and color invariance model are used; 2) The fully affine invariant local feature regions are built based on probability density Hessian matrix; and 3) The invariant significant bitplane histograms are introduced to embed digital watermark. The extensive experimental works are carried out on a color image set collected from Internet, and the preliminary results show that the proposed watermarking approach can survive numerous kinds of distortions, including common image processing operations and desynchronization attacks.     

Rotation invariant watermark embedding based on scale-adapted characteristic regions

Rotation invariance is one of the most challenging issues in robust image watermarking. This paper presents two rotation invariant watermark embedding schemes in the non-subsampled contourlet transform (NSCT) domain based on the scale-adapted local regions. Watermark synchronization is achieved using the scale-space feature point based local characteristic regions. The first method embeds a binary watermark sequence by partitioning the local regions in a rotation invariant pattern. The second method embeds a binary watermark image in a content based manner, and the watermark signal is adaptive to the orientation of the image. Both methods achieve rotation invariant embedding by only using the rotation normalizing angle, thus no interpolation operation is performed. Extensive simulation results and comparisons show that the proposed schemes can efficiently resist both signal processing attacks and geometric attacks.     

基于尺度不变特征的脊波域量化水印算法

针对传统数字水印算法抵抗旋转、缩放等几何攻击能力较弱的问题,提出一种基于尺度不变特征的脊波域量化水印算法.利用尺度不变特征变换构造稳定的图像局部区域,对局部区域实施脊波变换,选择能量较大方向上的脊波细节系数,利用量化索引调制策略嵌入水印信息.仿真结果表明,该算法具有较好的检测性能,在抗压缩、叠加噪声、缩放、剪切等攻击方面具有较强的鲁棒性.     

A self-adaptive image normalization and quaternion PCA based color image watermarking algorithm

This paper proposes a novel robust digital color image watermarking algorithm which combines color image feature point extraction, shape image normalization and QPCA (quaternion principal component algorithm) based watermarking embedding (QWEMS) and extraction (QWEXS) schemes. The feature point extraction method called Mexican Hat wavelet scale interaction is used to select the points which can survive various attacks and also be used as reference points for both watermarking embedding and extraction. The normalization shape image of the local quadrangle image of which the four corners are feature points of the original image is invariant to translation, rotation, scaling and skew, by which we can obtain the relationship between the feature images of the original image and the watermarked image which has suffered with geometrical attacks. The proposed QWEMS and QWEXS schemes which denote the color pixel as a pure quaternion and the feature image as a quaternion matrix can improve the robustness and the imperceptibility of the embedding watermarking. To simplify the eigen-decomposition procedure of the quaternion matrix, we develop a calculation approach with which the eigen-values and the corresponding eigen-vectors of the quaternion matrix can be computed. A binary watermark image is embedded in the principal component coefficients of the feature image. Simulation results demonstrate that the proposed algorithm can survive a variety of geometry attacks, i.e. translation, rotation, scaling and skew, and can also resist the attacks of many signal processing procedures, for example, moderate JPEG compression, salt and pepper noise, Gaussian filtering, median filtering, and so on.     

基于SVD局部数字水印算法

本文将水印嵌入和局部不易发生变化的特征点结合,首先利用多尺度Harris角点检测算法检测出图像的特征点;其次以局部最稳定的特征点为中心选取局部特征区域;最后对特征区域分块,利用奇异值分解后最大奇异值的稳定性,将水印嵌入在最大的奇异值上。实验证明,该算法不仅具有很好的不可见性,而且对一些图像攻击具有很好的鲁棒性,尤其是局部攻击。     

A feature-based robust digital image watermarking against desynchronization attacks

In this paper,a new content-based image watermarking scheme is proposed.The Harris-Laplace detector is adopted to extract feature points,which can survive a variety of attacks.The local characteristic regions (LCRs) are adaptively constructed based on scale-space theory.Then,the LCRs are mapped to geometrically invariant space by using image normalization technique.Finally, several copies of the digital watermark are embedded into the nonoverlapped LCRs by quantizing the magnitude vectors of discrete Fourier transform (DFT) coefficients.By binding a watermark with LCR,resilience against desynchronization attacks can be readily obtained.Simulation results show that the proposed scheme is invisible and robust against various attacks which includes common signals processing and desynchronization attacks.