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。     

Robust image watermarking using sample area quantization

Digital watermarking is a way to protect the intellectual property of digital media. Among different algorithms, Quantization Index Modulation (QIM) is one of the popular methods in designing a watermark system. In this paper, a sample area quantization method is proposed for robust watermarking of digital images. First, the samples of the host signal form a polygon and low frequency wavelet coefficients of the carrier image is considered as the host sample. A watermark digit is embedded by quantizing the area of the polygon. Then, in order to minimize the distortion, the watermarked samples are obtained as close as possible to the host samples by solving an optimization problem while maintaining the quantized area at its fixed value. The optimization problem is solved using the gradient descend method. Finally, a maximum likelihood detector is designed to extract the watermark digits, assuming a Gaussian distribution for the host signal samples. The performance of the proposed method is theoretically obtained in terms of error probability in the presence of additive white Gaussian noise. Theoretical results are verified using simulation with artificial signals. The proposed method is compared to the state-of-the-art method under different attacks including: noise addition, JPEG compression, filtering, and geometrical attacks. The results confirm that the proposed method outperforms the other ones in terms of error probability against different attacks. The results also show that in the trade-off between robustness, distortion and capacity, by decreasing capacity the two other factors could be improved simultaneously.

     

An algorithm for robust image watermarking based on the DCT and Zernike moments

An image watermarking scheme in the 2D DCT domain is proposed by exploring the advantages of using Zernike moments. Zernike transform has been used in image processing applications such as image recognition, authentication, protection, etc. Here, we propose to use the Zernike moments of the DCT transform to provide an efficient watermarking method. Particularly, the novelty of the proposed approach relies on the method for selection of features that will enable both preserving the image quality and robustness to attacks. Also, a criterion for selection of image blocks suitable for watermarking is given. It is based on the ? ₁-norm of Zernike moments. The efficiency of the proposed watermarking algorithm is proved on several examples considering different types of attacks (compression, noise, filtering, geometrical attacks).     

Robust hashing for image authentication using SIFT feature and quaternion Zernike moments

A novel robust image hashing scheme based on quaternion Zernike moments (QZMs) and the scale invariant feature transform (SIFT) is proposed for image authentication. The proposed method can locate tampered region and detect the nature of the modification, including object insertion, removal, replacement, copy-move and cut-to-paste operations. QZMs considered as global features are used for image authentication while SIFT key-point features provide image forgery localization and classification. Proposed approach performance were evaluated on the color images database of UCID and compared with several recent and efficient methods. These experiments show that the proposed scheme provides a short hash length that is robust to most common image content-preserving manipulations like large angle rotations, and allows us to correctly locating forged image regions as well as detecting types of forgery image.

     

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.     

基于Zernike不变矩的零水印算法

为了实施图像的版权保护,提出了一种基于Zernike不变矩的零水印算法。利用Zernike矩幅度的旋转不变性提取图像特征点,将特征点通过设定的阈值量化为二值序列作为零水印保存到零水印信息库（IPR）。证明版权利用Zernike矩提取待检测图像特征点,以同样的阈值量化为二值水印序列与零水印作相关性检测。实验结果表明,该方法很好地解决了传统水印鲁棒性和不可感知性的矛盾问题,对常用的图像处理和几何攻击具有较好的鲁棒性。     

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。     

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.     

基于傅里叶-梅林矩的抗几何攻击图像水印算法

如何有效抵抗几何攻击是数字图像水印研究领域的热点问题之一,一个微弱不可觉察的几何攻击就可能使绝大多数水印算法失效。以不变矩理论为基础,提出了一种基于正交傅里叶-梅林矩的可有效抵抗几何攻击的图像水印新算法。结合傅里叶-梅林矩的几何不变特性,计算出原始图像的傅里叶-梅林矩;根据稳定矩的选取规则选取部分稳定的傅里叶-梅林矩,采用量化调制策略将水印信息嵌入到所选矩的幅值中;将傅里叶-梅林矩修改前后的重构差值图像叠加到原始载体图像中,得到含水印图像。仿真实验表明,该算法不仅具有较好的不可感知性,而且对常规信号处理和几何攻击均具有较好的鲁棒性。     

基于Radon变换不变矩的鲁棒性数字水印技术

现有的大多数数字水印算法在设计时过分地强调载体数据中嵌入水印以及在遭受几何攻击之后水印的不可感知性和鲁棒性,而对水印在检测时数字水印的虚警率和漏检率实验分析甚少。如果一个数字水印算法在水印检测时它的虚警率和漏检率很高,即使这种算法具有很好的鲁棒性那么也不能有效地解决版权保护,相反却会引入新的版权纠纷。针对以上提出的问题,提出一种基于Radon变换不变矩的抗几何攻击鲁棒性数字水印可以有效地减少水印的漏检和误检问题。本算法使用Radon变换构建矩不变量,首先使用小波变换的多尺度分析的特性,提取小波分解后的低频逼近子图;其次采用图像置乱的方法消除低频逼近子图像素之间的空间相关性,并通过零像素值模板背景图像代替图像尺度大小归一化;然后将置乱后的低频子图加载到零像素值模板背景图像上;最后使用Radon变换不变矩来设计水印和检测水印。经过仿真实验证明,该方法对于旋转,缩放,平移等攻击具有很好鲁棒性的同时,对于普通的加噪,滤波,JPEG压缩攻击也具有很好的鲁棒性,且具有极低误检率。     

Robust color image watermarking using multiple fractional-order moments and chaotic map

Multimedia Tools and Applications - Robust watermarking is an effective method and a promising solution for securing and protecting the copyright of digital images. Moments and moment invariants...     

基于不变矩的抗旋转、缩放、平移鲁棒性数字水印

目前的数字图像水印对于加噪、滤波、JPEG压缩攻击具有很好的鲁棒性但抗几何类攻击仍是对数字图像水印的一个巨大挑战。将水印嵌入到图像中的不变域中,这是一种比较好的方法。然而,由于嵌入水印的原始图像和受到几何攻击后（RST变换）的图像尺度大小发生了改变,这就使得水印的嵌入和检测之间失去了同步,从而导致水印检测的失败。为了解决图像尺度大小在水印嵌入和检测时发生改变的问题,提出了一种使用零像素值模板背景图像和不变矩抗旋转、缩放、平移鲁棒性数字水印。通过零像素值模板背景图像代替图像尺度大小归一化,同时使用几何不变矩来设计水印和检测水印。经过仿真实验证明,该方法对于普通的加噪、滤波、JPEG压缩攻击具有很好鲁棒性的同时,对于旋转、缩放、平移等攻击也具有很好的鲁棒性,是一种简单、实用、可靠的数字水印方法（使用的仿真软件：Matlab 7.1）。     

Feature extraction and local Zernike moments based geometric invariant watermarking

A robust and geometric invariant digital image watermarking scheme based on robust feature detector and local Zernike transform is proposed in this paper. The robust feature extraction method is proposed based on the Scale Invariant Feature Transform (SIFT) algorithm, to extract circular regions/patches for watermarking use. Then a local Zernike moments-based watermarking scheme is raised, where the watermarked regions/patches can be obtained directly by inverse Zernike Transform. Each extracted circular patch is decomposed into a collection of binary patches and Zernike transform is applied to the appointed binary patches. Magnitudes of the local Zernike moments are calculated and modified to embed the watermarks. Experimental results show that the proposed watermarking scheme is very robust against geometric distortion such as rotation, scaling, cropping, and affine transformation; and common signal processing such as JPEG compression, median filtering, and low-pass Gaussian filtering.     

条件数和Zernike矩在图像配准中的应用

提出了一种基于条件数和泽尼克矩的图像配准算法。首先用Harris角点检测器提取特征点并通过条件数去掉一些伪特征点;用改进的Zernike矩作为特征点的描述子,通过比较各个特征点圆形邻域泽尼克矩的欧式距离得到初始匹配点对;用RANSAC估计待配准图像和基准图像之间的变换参数,实验表明,该算法在图像存在比例缩放、旋转等情况下有很好的配准效果。     

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.     

An imperceptible semi-blind image watermarking scheme in DWT-SVD domain using a zigzag embedding technique

Multimedia Tools and Applications - This research work presents a semi-blind image watermarking scheme based on transforms domain DWT-SVD using an efficient embedding technique. This scheme...     

基于奇偶量化的Contourlet变换域指纹图像水印算法

提出了一种基于奇偶量化的Contourlet变换域指纹图像水印算法。原始指纹图像经过Contourlet变换后，分解为一系列多尺度、局部化、方向性的子带图像，选择在低频子带中嵌入经过二维Arnold置乱加密后的水印。嵌入水印时，采用奇偶量化算法修改低频子带的系数。水印提取时，不需要原始图像，实现了盲提取。实验结果表明，提出的指纹图像水印算法能够较好地抵抗JPEG有损压缩、叠加噪声、剪裁等攻击，具有较好的不可见性和鲁棒性，提高了指纹识别的可靠性。     

基于遗传算法的鲁棒数字水印技术

提出了一种增强水印鲁棒性的算法,该算法采用多目标优化的遗传算法定义一种新的适应度函数,结合Watson视觉感知模型,调节水印在DCT变换域嵌入的强度.根据遗传算法得到的不同结果,不同强度的水印信息被嵌入到各个DCT块的视觉感知门限(JND)最大的几个中低频系数中.实验结果表明,在满足水印不可见性的同时,算法在噪声、滤波、旋转,压缩等图像处理条件下具有很好的鲁棒性.