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.     

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.     

基于图像特征点的强鲁棒数字水印嵌入方案

提出了一种抵抗一般性几何攻击的数字水印新算法. 该算法首先利用多尺度 Harris 检测算子从载体图像中提取出稳定的特征点; 然后根据特征尺度自适应确定局部特征区域, 并对其实施归一化处理; 最后结合预失真补偿理论, 采纳 DFT 中频幅值比较策略将水印信息重复嵌入到多个归一化局部特征区域内. 仿真实验表明, 本文算法不仅具有较好的透明性, 而且对常规信号处理和一般性几何攻击均具有较好的鲁棒性.     

A New Digital Image Watermarking Algorithm Resilient to Desynchronization Attacks

Synchronization is crucial to design a robust image watermarking scheme. In this paper, a novel feature-based image watermarking scheme against desynchronization attacks is proposed. The robust feature points, which can survive various signal-processing and affine transformation, are extracted by using the Harris-Laplace detector. A local characteristic region (LCR) construction method based on the scale-space representation of an image is considered for watermarking. At each LCR, the digital watermark is repeatedly embedded by modulating the magnitudes of discrete Fourier transform coefficients. In watermark detection, the digital watermark can be recovered by maximum membership criterion. Simulation results show that the proposed scheme is invisible and robust against common signal processing, such as median filtering, sharpening, noise adding, JPEG compression, etc., and desynchronization attacks, such as rotation, scaling, translation, row or column removal, cropping, and random bend attack, etc.     

A feature-based robust digital image watermarking against geometric attacks

Based on scale space theory and an image normalization technique, a new feature-based image watermarking scheme robust to general geometric attacks is proposed in this paper. First, the Harris–Laplace detector is utilized to extract steady feature points from the host image; then, the local feature regions (LFR) are ascertained adaptively according to the characteristic scale theory, and they are normalized by an image normalization technique; finally, according to the predistortion compensation theory, several copies of the digital watermark are embedded into the nonoverlapped normalized LFR by comparing the DFT mid-frequency magnitudes. Experimental results show that the proposed scheme is not only invisible and robust against common signals processing methods such as median filtering, sharpening, noise adding, and JPEG compression etc., but also robust against the general geometric attacks such as rotation, translation, scaling, row or column removal, shearing, local geometric distortion and combination attacks etc.     

A robust digital audio watermarking scheme using wavelet moment invariance

It is a challenging work to design a robust audio watermarking scheme against various attacks. Wavelet moment invariances are new features combining the moment invariant features and the wavelet features, and they have some excellent characteristics, such as the ability to capture local information, robustness against common signal processing, and the linear relationship between a signal and its wavelet moments etc. Based on wavelet moment and synchronization code, we propose a new digital audio watermarking algorithm with good auditory quality and reasonable resistance against most attacks in this paper. Firstly, the origin digital audio is segmented and then each segment is cut into two parts. Secondly, with the spatial watermarking technique, synchronization code is embedded into the statistics average value of audio samples in the first part. And then, map 1D digital audio signal in the second part into 2D form, and calculate its wavelet moments. Finally, the watermark bit is embedded into the average value of modulus of the low-order wavelet moments. Meanwhile combining the two adjacent synchronization code searching technology, the algorithm can extract the watermark without the help from the origin digital audio signal. Simulation results show that the proposed watermarking scheme is not only inaudible and robust against common signals processing such as MP3 compression, noise addition, resampling, and re-quantization etc., but also robust against the desynchronization attacks such as random cropping, amplitude variation, pitch shifting, and jittering etc.     

A robust content based audio watermarking using UDWT and invariant histogram

Desynchronization attack is known as one of the most difficult attacks to resist, for it can desynchronize the location of the watermark and hence causes incorrect watermark detection. It is a challenging work to design a robust audio watermarking scheme against desynchronization attacks. Based on undecimated discrete wavelet transform (UDWT) and invariant histogram, we propose a new content based audio watermarking algorithm with good audible quality and reasonable resistance toward desynchronization attacks in this paper. Firstly, the undecimated discrete wavelet transform (UDWT) is performed on original host audio. Secondly, the invariant histogram is extracted from a selected wavelet coefficients range in the low frequency subband. Then, the bin of histogram is divided into many groups, each group including four consecutive bins. For each group, one watermark bit is embedded by reassigning the number of wavelet coefficients in this group of four bins. Finally, the digital watermark is embedded into the original audio signal in UDWT domain by modifying a small set of wavelet coefficients. Simulation results show that the proposed watermarking scheme is not only inaudible and robust against common signal processing operations such as MP3 compression, noise addition, and low-pass filtering etc, but also robust against the desynchronization attacks such as random cropping, time-scale modification, pitch shifting, and jittering etc.     

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.     

图像归一化与伪Zernike矩的鲁棒水印算法研究*

以基于矩的图像归一化技术及伪Zernike矩相关知识为基础,提出一种可有效抵抗几何攻击的数字水印新算法。算法首先利用归一化技术将原始图像映射到几何不变空间内;然后结合不变质心理论提取出归一化图像的重要区域;最后通过量化调制伪Zernike矩幅值将水印嵌入到重要区域中。仿真实验表明,该算法不仅具有较好的透明性,而且对常规信号处理(滤波、锐化、加噪和JPEG压缩等)和几何攻击(全局仿射变换、局部失真等)均具有较好的鲁棒性。     

基于图像特征的数字水印算法研究

为了使数字水印具有更鲁棒的抗攻击能力，提出了一种基于图像特征的数字水印新算法。该算法首先利用Harris—Laplace算子提取载体图像特征点；然后结合特征尺度白适应确定局部特征区域；最后，采纳DFT中频幅值比较策略将数字水印信息重复嵌入到多个不相交的局部特征区域中。检测时，根据模糊模式识别的最大隶属度原则检测水印信息。仿真实验结果表明，该新算法不仅具有较好的透明性，而且对常规信号处理（中值滤波、边缘锐化、叠加噪声和JPEG压缩等）和去同步攻击（旋转、平移、缩放、行列去除、剪切和局部随机弯曲等）均具有较好的鲁棒性。     

基于图像特征的鲁棒水印算法研究

为提高图像盲水印抗几何攻击的能力,提出了一套基于图像特征的水印嵌入方案。首先利用具有几何不变性的Harris算子检测出图像特征点,然后在每块由特征点生成的Delaunay三角网上采用一种基于小波系数显著性差异调制量化方式进行水印的嵌入和检测。该嵌入水印算法的思想是通过比较每组小波系数的显著性差异值和所有组的平均显著性差异值的方法来量化每一组块的最大小波系数。实验结果表明,该方法不仅对压缩、滤波等常见攻击具有稳健性,同时对旋转、缩放、变形等几何攻击也具有较好的稳健性。     

一种基于多尺度空间的图像水印算法

当前数字水印对常见的图像处理攻击如高斯噪声、中值滤波、有损压缩等具有较强的抵抗能力,但其抵抗剪切、缩放等几何攻击的能力较差。因此,为提高数字水印的鲁棒性,结合尺度不变特征变换算子和视觉感知模型,提出一种基于不变特征的水印嵌入方法。基于广义高斯分布模型对小波系数进行刻画,并根据二值假设检验理论确定水印的检测阈值,由此进一步给出水印虚警和漏警之间的工作特性曲线关系。实验仿真结果表明提出的水印方法在抗压缩、叠加噪声、缩放、剪切、旋转等攻击时具有较好的鲁棒性能。     

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     

两种抗几何攻击数字图像水印算法分析及比较

以图像归一化和不变质心理论为基础提出了两种安全性较高的数字图像水印算法。为了增加水印的隐秘性及抗干扰能力,水印在嵌入前均进行了置乱和混沌加密处理,然后两种方案分别根据其归一化图像的不变质心确定出相应的重要区域,并在该区域实施水印的嵌入。实验结果表明,提出的两种数字图像水印算法均具有较好的不可感知性和抗攻击的鲁棒性,且在抵抗常规信号处理和几何攻击下各具优势。     

基于SIFT的椭圆区域鲁棒数字水印方案

如何有效抵抗去同步攻击是数字图像水印研究领域的热点问题之一。利用图像仿射协变特征,提出一种可有效抵抗去同步攻击的鲁棒水印算法。对目前流行的利用多尺度Harris和SIFT描述算子来匹配图像的方法,后者有较好的匹配效果,对恢复同步水印更加稳定,并且能较好抵抗去同步攻击。该算法利用性能稳定的SIFT算子提取图像特征点,并通过基于最小生成树聚类算法的选择策略获得一组稳定且彼此独立的椭圆仿射协变特征区域,基于特征区域,利用椭圆归一化得到具有缩放和旋转不变性的圆形区域。将圆形区域进行非下采样轮廓变换（NSCT）,其中非下采样轮廓变换不仅克服了小波（Wavelet）变换的非奇异性最优基缺点,而且提供了优于轮廓（Contourlet）变换的平移不变性。将水印嵌入变换后的低频子带中。该算法实现盲提取,仿真实验结果表明,提出的算法是有效的且对常规图像处理、几何攻击以及组合攻击均具有较好的鲁棒性。     

尺度不变特征点在局部图像水印算法中的应用

局部图像水印算法,将水印以图像特征为参照点嵌入到各个局部区域中,因此是一种抗几何攻击的有效方法.为了使得各个用于嵌水印的局部区域在水印检测过程中能准确地再现,作为参照点的特征必须是鲁棒的.本文利用尺度不变特征点作为同步水印的参照点.为了使得参照点的分布均匀、稳定,我们通过自适应的邻域半径来从尺度不变特征点中筛选出用于同步水印的参照点.将筛选出的特征点作为顶点生成Delaurmy三角网,将三角网中的每一个三角形作为一个用于嵌水印的局部区域.实验结果表明,经过一般的信号处理攻击及旋转、缩放、裁剪和轻微的纵横比改变等几何攻击后,用于嵌水印的局部区域大多能准确地再现,利用尺度不变特征点来同步水印是可行的.     

A new adaptive digital audio watermarking based on support vector machine

It is a challenging work to design a robust digital audio watermarking scheme against desynchronization attacks. On the basis of support vector machines (SVMs), a new robust digital audio watermarking algorithm against desynchronization attacks is proposed in this paper, and in this the audio statistics characteristics and synchronization code are utilized. Firstly, the optimal embedding positions are located adaptively by using the SVM theory. Secondly, the 16-bit Barker code is chosen as synchronization mark and embedded into the digital audio by modifying the statistics average value of several samples. Finally, the digital watermark are embedded into the statistics average value of low-frequency components in wavelet domain by making full use of auditory masking. Experimental results show that the proposed scheme is inaudible and robust against common signal processing such as MP3 compression, low-pass filtering, noise addition, equalization, etc., and is robust against desynchronization attacks such as random cropping, amplitude variation, pitch shifting, time-scale modification, jittering, etc.     

基于支持向量机的鲁棒盲水印算法

提出了一种基于支持向量机的鲁棒盲水印算法.该算法首先用多尺度Harris-Laplace检测算子从载体图像中提取出稳定的特征点,然后根据特征自适应确定局部特征区域,在特征区域选择一些点作为嵌入水印的点,结合图像的邻域相关性,根据灰度图像特点,选取特征向量作为SVR训练模型,进而利用SVR进行预测,调节嵌入点的像素值进行水印的嵌入和提取.实验结果表明,用该技术嵌入水印后的图像具有很好的图像感知质量,时常规信号处理乖去同步攻击特别是JPEG压缩具有较强的鲁棒性.     

Robust image watermarking technique using triangular regions and Zernike moments for quantization based embedding

Watermarking is a tool to embed information in the image to provide authentication, copyrights protection, copy control, etc. Some watermarking techniques are robust to intentional /unintentional attacks on the watermarked image. In this study, we propose a robust watermarking approach that can resist geometrical attacks. The proposed technique exploits both the robust image feature points and local Zernike moments for embedding the information. Delaunay tessellation is employed to divide image into distinct triangular segments based on robust features. These features are identified using Harris detector. Zernike moments are calculated for each selected triangular segment, and then the watermark is embedded in the magnitude of Zernike moments using dither modulation. It can be observed from the experimental results that by using proposed approach, the watermark can be detected even in the presence of geometrical distortion, i.e. rotation, cropping, and scaling, and JPEG compression attack.