可有效抵抗一般性几何攻击的数字水印检测方法

以回归型支持向量机理论为基础, 结合性能稳定的伪Zernike矩和Krawtchouk矩, 提出了一种可有效抵抗一般性几何攻击的强鲁棒数字图像水印检测算法. 该算法首先选取图像的低阶Krawtchouk矩作为特征向量, 然后利用SVR对几何变换参数进行训练学习并对待检测图像进行数据预测, 最后对其进行几何校正并提取水印信息. 仿真实验结果表明, 该数字图像水印检测算法不仅具有较好的不可感知性, 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.     

一种基于SVR几何校正的数字水印检测算法

以回归型支持向量机（SVR）理论基础,提出了一种可有效抵抗几何攻击的图像水印检测新算法.该算法首先选取图像的组合矩作为特征向量,并通过SVR对旋转、缩放、平移等几何变换参数进行训练学习,以获得SVR训练模型;然后利用SVR训练模型对待检测图像进行数据预测,并结合预测输出结果对其进行几何校正;最后从已校正数字图像内提取出水印信息.仿真实验结果表明,本文算法对常规信号处理（滤波、叠加噪声、JPEG压缩等）和几何攻击（旋转、缩放、平移、剪切等）均具有较好的鲁棒性。     

A new SVM-based image watermarking using Gaussian-Hermite moments

Geometric 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 image watermarking scheme against geometric attacks. Based on the support vector machine (SVM) and Gaussian-Hermite moments (GHMs), we propose a robust image watermarking algorithm in nonsubsampled contourlet transform (NSCT) domain with good visual quality and reasonable resistance toward geometric attacks in this paper. Firstly, the NSCT is performed on original host image, and corresponding low-pass subband is selected for embedding watermark. Then, the selected low-pass subband is divided into small blocks. Finally, the digital watermark is embedded into host image by modulating adaptively the NSCT coefficients in small block. The main steps of digital watermark detecting procedure include: (1) some low-order Gaussian-Hermite moments of training image are computed, which are regarded as the effective feature vectors; (2) the appropriate kernel function is selected for training, and a SVM training model can be obtained; (3) the watermarked image is corrected with the well trained SVM model; (4) the digital watermark is extracted from the corrected watermarked image. Experimental results show that the proposed image watermarking is not only invisible and robust against common image processing operations such as filtering, noise adding, JPEG compression, etc., but also robust against the geometric attacks.     

Robust digital watermarking in PDTDFB domain based on least squares support vector machine

Geometric distortion 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 image watermarking scheme against geometric distortions. Based on the least squares support vector machine (LS-SVM) geometric distortions correction, we propose a new image watermarking scheme in shiftable complex directional pyramid (PDTDFB) domain with good visual quality and reasonable resistance toward geometric distortions in this paper. Firstly, the PDTDFB decomposition is performed on the original host image. Then, the corresponding lowpass subband is divided into small blocks. Finally, the digital watermark is embedded into host image by modulating the selected lowpass PDTDFB coefficients in small blocks. The main steps of digital watermark detecting procedure include: (1) the PDTDFB decomposition is performed on the test images, and some low-order Gaussian–Hermite moment energy of highpass subbands are computed, which are regarded as the effective feature vectors; (2) the appropriate kernel function is selected for training, and a LS-SVM training model can be obtained; (3) the watermarked image is corrected with the well trained LS-SVM model; and (4) the digital watermark is extracted from the corrected watermarked image. Experimental results show that the proposed image watermarking is not only invisible and robust against common image processing operations such as filtering, noise adding, and JPEG compression etc, but also robust against the geometrical distortions.     

A novel color image watermarking scheme in nonsampled contourlet-domain

Geometric distortion 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 color image watermarking scheme against geometric distortions. Based on the support vector regression (SVR) and nonsubsampled contourlet transform (NSCT), we propose a new color image watermarking algorithm with good visual quality and reasonable resistance toward geometric distortions in this paper. Firstly, the geometrically invariant space is constructed by using color image normalization, and a significant region is obtained from the normalized color image by utilizing the invariant centroid theory. Then, the NSCT is performed on the green channel of the significant region. Finally, the digital watermark is embedded into host color image by modifying the low frequency NSCT coefficients, in which the HVS masking is used to control the watermark embedding strength. In watermark detection, according to the high correlation among different channels of the color image, the digital watermark can be recovered by using SVR technique. Experimental results show that the proposed color image watermarking is not only invisible and robust against common image processing operations such as filtering, noise adding, and JPEG compression etc., but also robust against the geometrical distortions.     

基于奇异值分解和小波变换的抗几何失真数字水印新方法

目前,大多数鲁棒图像水印所面临的最大问题就是几何攻击,而现有水印技术大都难以抵抗几何变换类攻击,如旋转、尺度变换等,由于几何攻击破坏了水印分量的同步,即使微小幅度的图像旋转或尺度变换都可能导致水印检测过程失败.提出了一种基于奇异值分解和小波变换的方法来盲提取受到几何攻击后的图像中的水印,即利用了奇异值对几何失真的稳健性,又利用了小波变换对一般攻击的稳健性.实验证明,提出的方法对几何攻击具有很好的鲁棒性.     

Geometrically invariant color image watermarking scheme using feature points

Geometric distortion is known as one of the most difficult attacks to resist. Geometric distortion desynchronizes the location of the watermark and hence causes incorrect watermark detection. In this paper,we propose a geometrically invariant digital watermarking method for color images. In order to synchronize the location for watermark insertion and detection,we use a multi-scale Harris-Laplace detector,by which feature points of a color image can be extracted that are invariant to geometric distortions. ...     

基于NSST变换与粒子群优化的鲁棒水印算法

为增强水印图像的视觉隐秘性并抵御几何失真能力,设计NSST变换耦合粒子群优化的鲁棒水印算法。提取图像对应的Y(亮度)、U(色度)、V(浓度)成分;引入非下采样Shearlet变换(nonsubsampled Shearlet transform,NSST),对Y、U和V实施分解,形成对应的低频子带,将其分割为若干个子块;建立粒子群算法的适应度函数,优化子块的嵌入强度;构建水印嵌入方法,将水印信息隐藏到NSST系数中;构建训练图像集,计算这些样本的多元极谐变换(quaternion polar harmonic transorm,QPHT)矩,从中确定8个QPHT系数;训练支持向量机,预测攻击参数;构建水印检测方法,从校正图像中提取水印。测试数据表明,较已有的鲁棒水印技术而言,所提方案具有更高的不可感知性与抵御几何攻击的能力。     

基于第二代Bandelet变换的抗几何攻击图像水印

抗几何攻击的鲁棒图像水印设计是目前水印技术研究的难点和热点之一. 文中分析了图像的Bandelet变换特性, 提出了一种以图像特征点矢量集为特征向量的回归支持向量机(Support vector regression, SVR)和第二代 Bandelet变换的抗几何攻击图像水印算法,采取的主要方法包括: 1)在Bandelet变换提取的刻画图像局部特征的几何流系数上, 采用奇偶量化嵌入水印; 2)利用Harris-Laplace算子从归一化的含水印图像中提取具有几何形变鲁棒性的图像特征点,构造特征点矢量集 作为特征向量,应用回归支持向量机对几何变换参数进行训练学习; 3)水印检测时, 先利用SVR训练模型得到待检测图像所受几何攻击的参数并作几何校正,然后通过奇偶检测器盲提取水印.仿真实验表明,所提出的水印算 法不仅具有良好的透明性,而且对常规图像处理、一般性几何攻击和组合攻击均具有良好的鲁棒性.     

基于回归型支持向量机的数字图像水印新算法

以回归型支持向量机（Support Vector Regression,SVR）理论为基础,提出一种数字图像水印新算法.该算法能够结合图像局部相关性,选取稳定的特征向量并获得SVR训练模型,进而利用SVR训练模型嵌入和提取数字水印信息.该算法以保证不可感知性和鲁棒性的良好平衡为前提,实现了数字水印的盲检测.仿真实验表明,本文算法不仅具有较好的不可感知性,而且对叠加噪声、JPEG压缩、锐化、平滑滤波、对比度增强等常规处理及扭曲、剪切等几何攻击均具有较好的鲁棒性,其整体性能明显优于现有SVM图像水印方案.     

Geometrically invariant image watermarking using SVR correction in NSCT domain

Based on the support vector regression (SVR) geometric distortions correction, we propose a robust image watermarking algorithm in nonsubsampled contourlet transform (NSCT) domain with good visual quality and reasonable resistance toward geometric attacks in this paper. Firstly, the NSCT is performed on original host image, and corresponding low-pass subband is selected for embedding watermark. Then, the selected low-pass subband is divided into small blocks. Finally, the digital watermark is embedded into host image by modulating the NSCT coefficients in small blocks. In digital watermark detecting procedure, the SVR geometrical distortions correction is utilized. Experimental results show that the proposed image watermarking is invisible, and robust against common image processing and some geometrical attacks.     

基于直方图调整的抗几何攻击图像水印

几何攻击被公认为是数字图像水印技术走上商用的瓶颈之一。本文根据图像几何变换过程中灰度值统计特征的稳定性原理,提出了一种基于直方图调整的抗几何攻击数字图像水印算法。首先根据图像灰度均值选取一个灰度区间,然后通过调整位于该灰度区间内的图像直方图来嵌入水印信息。在提取水印时无需提供原始图像,实现盲检测。实验结果表明本算法不仅具有很好的隐蔽性,而且对诸如旋转、缩放、平移、仿射变换、剪切等几何攻击和常规信号处理均具有很强的鲁棒性。     

A new robust digital watermarking based on exponent moments invariants in nonsubsampled contourlet transform domain

Geometric distortions are usually difficult for watermark to survive. It is a challenging work to design a robust image watermarking scheme against geometric distortions. Exponent moments (EMs) is a new kind of orthogonal moment defined on the circular domain. EMs are free of numerical instability so that high order moments can be computed accurately. The modulus of EMs is invariant to geometric transformation. In this paper, we propose a new robust image watermarking based on EMs invariants in nonsubsampled contourlet transform (NSCT) domain. Firstly, the NSCT, which has better directional frequency localization and a fast implementation, is applied on host image. Secondly, the EMs of the low-pass NSCT subband are computed, and the accurate EMs are selected. Finally, the digital watermark is embedded by quantizing the modulus of the selected EMs. Experimental results confirm the validity of our approach and its higher robustness against geometric distortions.     

一种新的基于伪Zernike矩的图像盲水印算法

抵抗几何攻击的鲁棒性是目前数字水印技术中的热点也是难点。提出一种新的基于伪Zernike矩的图像盲水印算法,首先计算图像归一化后的伪Zernike矩,然后选取部分合适的矩通过量化调制嵌入水印信息。水印提取时,利用伪Zernike矩的相位信息估计旋转角度进行几何校正,以提高矩的几何不变性。实验结果表明,本算法对于抗几何攻击尤其是旋转攻击具有很好的鲁棒性,同时也能抵抗常规的信号处理攻击。     

一种基于Krawtchouk矩的水印算法

提出一种基于Krawtchouk矩的水印算法,通过修改一些原始Krawtchouk矩并重构图像以获得水印图像.基于Krawtchouk矩与几何矩的关系,提出采用具有平移、比例缩放和旋转不变性的几何不变矩来检测水印.实验表明,与用Krawtchouk不变矩检测相比,该算法对于大角度旋转和图像平移的几何攻击具有更好的鲁棒性.     

Robust color image watermarking using invariant quaternion Legendre-Fourier moments

In this paper, a geometrically invariant color image watermarking method using Quaternion Legendre-Fourier moments (QLFMs) is presented. A highly accurate, fast and numerically stable method is proposed to compute the QLFMs in polar coordinates. The proposed watermarking method consists of three main steps. First, the Arnold scrambling algorithm is applied to a binary watermark image. Second, the QLFMs of the original host color image are computed. Third, the binary digital watermark is embedding by performing the quantization of selected QLFMs. Two different groups of attacks are considered. The first group includes geometric attacks such as rotation, scaling and translation while the second group includes the common signal processing attacks such as image compression and noise. Experiments are performed where the performance of proposed method is compared with the existing moment-based watermarking methods. The proposed method is superior over all existing quaternion moment-based watermarking in terms of visual imperceptibility capability and robustness to different attacks.     

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Krawtchouk不变矩和SVD-LWT的双重水印研究

为提高数字图像水印的鲁棒性和透明性,提出了一种基于Krawtchouk不变矩、奇异值分解(SVD)和提升小波变换(LWT)的彩色图像双水印算法。该算法首先从载体RGB图像中提取绿色分量进行两级提升小波变换,利用Krawtchouk不变矩对平移、旋转和缩放的不变性以及Krawtchouk矩良好的局部特性和重构性,计算其低频分量的Krawtchouk低阶矩不变量构造水印系统;然后对其变换后的中频分量奇异值进行分解,嵌入混沌置乱后的水印图像的奇异值作为另一水印系统。仿真实验结果表明,该算法不仅有良好的不可见性,而且对常见攻击和几何攻击都具有很好的鲁棒性,并具有一定的应用价值。     

Geometric attack resistant image watermarking based on MSER

Geometric distortions are simple and effective attacks rendering many watermarking methods useless. They make detection and extraction of the embedded watermark difficult or even impossible by destroying the synchronization between the watermark reader and the embedded watermark. In this paper, we propose a blind content-based image watermarking scheme against geometric distortions. Firstly, the MSER detector is adopted to extract a set of maximally stable extremal regions which are affine covariant and robust to geometric distortions and common signal processing. Secondly, every original MSER is fitted into an elliptical region that was proved to be affine invariant. In order to achieve rotation invariance, an image normalization process is performed to transform the elliptical regions into circular ones. Finally, watermarks are repeatedly embedded into every circular disk by modifying the wavelet transform coefficients. Experimental results on standard benchmark demonstrate that the proposed scheme is robust to geometric distortions as well as common signal processing.     

抗随机几何失真攻击的音频水印方案

随机几何失真攻击是指在数字音频中恶意地插入跳跃,或通过重采样等手段使相位等特性发生随机抖动,从而对音频数字水印构成严重威胁的行为。为防止这种攻击提出了一种利用音频信号采样点之间的相关性,同时根据信号局部特征生成水印信号并进行自同步嵌入的新方案。实验表明,该方案不仅对一般信号处理具有稳健性,也能够很好地抵御随机几何失真攻击。