抗几何攻击图像水印方案

几何形变一直是各类数字水印算法较难抵抗的攻击手段。针对此问题,提出一种抗几何攻击数字图像水印算法。采用周期性的水印嵌入图像,强度由NVF函数确定。在检测时,用白化滤波器对图像进行预处理。由于水印数据是随机的,而图像数据高度相关,白化滤波器起到增加水印数据能量,同时降低图像数据能量的作用。由理论计算得出选择滤波器的原则。然后,通过自相关检测,得到反映几何形变的峰值点。对实验结果的分析证明,该算法对各类几何攻击都能够精确定位。     

基于噪声分析的混沌数字图像水印算法

本文提出了一种具有较强鲁棒性的混沌数字图像水印算法.首先,根据特定的初始条件和参数产生混沌序列,从而构造出数量大、保密性好、自相关性强、互相关性弱的数字水印信号.对于水印的嵌入,根据小波分解后高频系数的能量来决定水印嵌入的区域,进而根据各层可容纳的噪声信号强度来控制水印的嵌入强度.水印的检测过程中先对图像进行几何配准,能够有效的提高水印检测的准确性.实验证明该水印嵌入算法易于实现,且具有较强的鲁棒性及视觉上的难以感知性.     

基于匹配滤波的有意义图像水印算法

图像隐形水印是解决数字媒体版权保护的有效手段.目前的大多数水印算法采用伪随机序列构成水印,因而只能给出"Yes"(有水印)或"No"(无水印)的回答.嵌入有意义的水印在一些应用场合更加重要,但同时也带来了更多的困难.嵌入有意义的水印必须解决二个问题:(1)嵌入的水印具有一定的数据量;(2)从有失真的水印图像中正确地提取嵌入的水印.本文应用数字通信的理论和方法,提出了一个嵌入有意义字符串的DCT域隐形水印算法.该算法采用BCH编码和匹配滤波来降低误码率.应用所提出的算法,把一个32个字符组成的水印嵌入到256×256的图像中并达到了较好的稳健性.在水印图像信噪比受Gaussian加性噪声干扰下降到26dB时,仍实现了对嵌入水印零错误概率的检测.     

基于噪声分析的混浊数字图像水印算法

本文提出了一种具有较强鲁棒性的混沌数字图像水印算法。首先,根据特定的初始条件和参数产生混沌序列,从而构造出数量大、保密性好、自相关性强、互相关性弱的数宇水印信号。对于水印的嵌入,根据小波分解后高频系数的能量来决定水印嵌入的区域,进而根据各层可容纳的噪声信号强度来控制水印的嵌入强度。水印的检测过程中先对图像进行几何配准,能够有效的提高水印检测的准确性。实验证明该水印嵌入算法易于实现,且具有较强的鲁棒性及视觉上的难以感知性。     

基于沃尔什-哈达玛变换和卷积编码的半脆弱水印算法

提出了一种基于沃尔什-哈达玛变换和卷积编码的半脆弱水印算法.在该算法中,对嵌入水印之前的图像进行像素块差分编码和卷积纠错编码来得到水印,并将其嵌入在沃尔什-哈达玛变换的图像能量值上;水印检测端通过检测卷积译码中产生的误码实现水印篡改定位,利用卷积译码的结果实现篡改图像的恢复.通过理论和实验分析了该算法的有效性和由此产生的误差.实验结果表明,本算法对于有损压缩具有良好的顽健性,可以精确地检测与定位篡改的图像区域,并且可以大致恢复原始图像内容.     

基于小波域的可见水印处理

本文提出一种小波域的自适应可见水印处理算法,该算法通过特殊设计的视觉模型,根据主图像和水印图像的特征,逐点确定水印嵌入的拉伸系数,从而使水印的嵌入程度依主图像和水印图像的特征变化而变化.实验表明,结果图像中的水印半透明地呈见在所覆盖的主图像区域,很好地保持了原始图像的细节,满足了对可见水印的一般性要求.     

基于Logistic混沌映射的DCT域脆弱数字水印算法

本文提出了一种新的混沌脆弱数字水印算法.利用混沌系统对初值的极端敏感性和块不相关水印技术,将图像DCT次高频系数和水印密钥合成为logistic混沌映射初值从而生成水印,再将水印嵌入到图像DCT的高频系数中得到水印图像.利用图像DCT系数之间的关系,实现了水印的盲检测.实验结果表明,该算法可以精确检测到对水印图像的一个像数点的改变,并具有良好的定位篡改能力.     

图像内容真实性认证的半易损水印方案研究

提出一种基于半易损的图像内容真实性认证方案。该算法既对不改变图像内容的一般性操作具有较好的顽健性，又能对改变图像内容的篡改操作具有较强的敏感性。在水印图像进行一般性处理后能够借助水印差别国和滑动窗检测并定位被篡改的区域。本文还从概率论的角度给出了精确的判决门限确定公式。仿真试验采用一般性操作和篡改操作相结合的方法，实验结果表明本文算法在保护数字图像内容真实性方面是可行的。     

DCT域下采样视频水印技术

根据DCT域Watson模型提出了一种抵抗下采样攻击的不可感知水印模型.用DCT域准卷积下采样方法得到图像的下采样版本,利用亮度特征和图像感知失真限制自适应确定被嵌入水印序列的区域、长度和强度,以使上采样水印图像具有良好的视觉效果和鲁棒性.实验结果表明该算法对噪声干扰及视频下采样具有较好的鲁棒性,而且不使用原始图像,就可进行水印的相关检测.     

基于交叉划分的灰度图像篡改检测与恢复算法

针对单像素篡改检测算法和分块篡改检测算法的缺点,提出了基于交叉划分的篡改检测与恢复算法.根据图像内容生成的2×2分块水印被两次嵌入到不同的对应块中,两次分块方式采用交叉划分方式.在水印嵌入时采用混沌映射序列对水印进行了加密.根据不同的分块位置进行两次篡改检测,并根据两次检测结果交叉后逐步求精,得到最终检测结果.图像恢复采用像素级恢复方式,先确定水印嵌入区域是否被篡改然后再根据两次嵌入的信息进行恢复.实验结果表明,该算法篡改检测定位精度可以达到像素级,恢复图像质量好,能够抵抗矢量攻击和噪声攻击.     

基于差错控制编码的水印检测

提出了一种基于差错控制编码(ECC)的水印检测方法,并且依据编码原理提出了进行水印检测的门限值的确定方法.基本思想是利用ECC对原始水印信息进行编码,水印检测时把提取出的待测编码水印与反馈水印进行比较,将其差值与设定的门限值进行比较,从而来判断水印存在与否.实验是基于DWT,采用的是ECC的Turbo码进行水印检测.仿真结果表明,该方法大大减少了水印图像在传输中的错误,水印的鲁棒性得到了极大的提高.     

Hiding digital watermarks using multiresolution wavelet transform

In this paper, an image accreditation technique by embedding digital watermarks in images is proposed. The proposed method for the digital watermarking is based on the wavelet transform. This is unlike most previous work, which used a random number of a sequence of bits as a watermark and where the watermark can only be detected by comparing an experimental threshold value to determine whether a sequence of random signals is the watermark. The proposed approach embeds a watermark with visual recognizable patterns, such as binary, gray, or color image in images by modifying the frequency part of the images. In the proposed approach, an original image is decomposed into wavelet coefficients. Then, multi-energy watermarking scheme based on the qualified significant wavelet tree (QSWT) is used to achieve the robustness of the watermarking. Unlike other watermarking techniques that use a single casting energy, QSWT adopts adaptive casting energy in different resolutions. The performance of the proposed watermarking is robust to a variety of signal distortions, such as JPEG, image cropping, sharpening, median filtering, and incorporating attacks     

基于双通道检测的多比特盲水印最优检测器的设计

水印检测错误会严重损害水印系统的可信度。该文提出基于双谱和能量检测的双通道检测来实现最优盲水印检测器的设计,并给出了一种在小波域中的具体实现。传统检测方法检测概率会随着信噪比的下降而急剧下降。双通道检测时信噪比很小时只要有足够大的双谱信息,即可得到较高的检测概率。即使双谱信息很小时双通道检测系统退化为似然比检测系统,仍是最优的。检测器检测到指定的水印后利用独立分量分析技术进行水印盲恢复。实验过程中攻击由通用水印测试软件Stirmark产生,实验数据证明所设计的最优盲检测器对Stirmark提供的各种攻击(如剪切、JPEG压缩、删行/列、旋转、尺度变换、随机几何攻击等)具有很好的鲁棒性。实验结果说明这种最优检测器的性能优越于现有的水印检测器。     

一种改进的基于DWT的彩色图像水印算法

文章介绍了数字水印的相关概念,结合HVS提出了一种改进的基于DWT彩色图像水印算法.首先对水印图像进行置乱加密预处理,提高了算法的安全性.然后计算绿色分量的数量,与预先设定的阈值进行比较,根据其关系选择不同的嵌入方式,将不同的色彩分量嵌入到不同的频带中.实验表明该算法在无视觉失真的条件下可以保证较好的嵌入量,且能有效抵抗常见的攻击,具有较好的鲁棒性.     

基于图像内容的脊波变换域数字水印模型和算法研究

在研究人类视觉(HVS)特性的基础上提出了一种在脊波变换域基于图像内容的数字水印模型。在此模型中,嵌入数字水印的强度归结于数字图像脊波系数的视觉掩盖效应,文中建立了脊波变换域人眼临界可见误差模型。图像的水印检测被归结为Neymann-PeaLrson准则下的统计模型,该模型被用来估算水印检测的最优阈值。作为算例,将临界可见误差模型结合扩展谱技术,提出了一种新颖的图像自适应水印算法,并给出了相应的实验结果。实验表明算法性能大幅度提高。     

Multimodal biometric image watermarking using two-stage integrity verification

In this paper, we propose multimodal biometric image watermarking scheme through a two-stage integrity verification method using the hidden thumbnail feature vectors for safe authentication of multimodal biometrics data, face and fingerprint, respectively. It is basically blind and spread spectrum-based robust watermarking method. The proposed method enables us to detect a tampered region by controlling watermark embedding strength to meet the requirement of predefined watermark extraction threshold. The key idea is that the thumbnail feature vectors of a face image as a watermark pattern are utilized by embedding into a fingerprint image in order to verify the integrity of respective biometric data. The first stage of integrity verification for a fingerprint image is done by deciding the validity of extracted thumbnail patterns. The second stage of integrity verification for a face image is done by one-to-one matching between the thumbnail feature vectors extracted from a face image and the thumbnail one of the received face image. Experimental results showed that the proposed method has a high detection rate of the forged biometric data and guarantees the security assurance.     

A combined just noticeable distortion model�Cguided image watermarking

Perceptual watermarking should take full advantage of the results from human visual system (HVS) studies. Just noticeable distortion (JND), which refers to the maximum distortion that the HVS does not perceive, gives us a way to model the HVS accurately. In this paper, we exploit a combined JND model, which represents an additional, accurate, perceptual visibility threshold profile to guide watermarking for digital images. The combined JND model-guided watermarking scheme, where visual models are fully used to determine image-dependent upper bounds on watermark insertion, allows us to provide the maximum strength transparent watermark. Experimental results confirm the improved performance of our combined JND model. Our combined JND model is capable of yielding higher injected-watermark energy without introducing noticeable distortion to the original image and outperforms the relevant existing visual models. Simulation results show that the proposed JND model-guided image watermarking scheme is more robust than other algorithms based on the relevant existing perceptual models while retaining the watermark transparency. At the same time, the proposed combined JND model has much lower computational complexity compared with the relevant existing perceptual models.     

抵抗几何攻击的数字图像水印

该文实现了一种抵抗几何攻击的数字图像水印方案。水印信号为根据密钥产生的服从正态分布的实数序列,对水印信号作预处理并进行周期化之后在空域将其嵌入数字图像中。检测端不需要原始图像,根据预测水印的自相关函数(ACF)判断水印图像遭受的几何变换攻击并进行逆变换,然后进行水印检测。实验表明该方案对压缩、滤波、剪切等常见的图像处理攻击同样具有很高的鲁棒性。     

Watermark detection for noisy interpolated images

In this brief, the case where the watermark is detected in a noisy interpolated version of the originally watermarked image is investigated. Polyphase decomposition is utilized at the detection side in order to enable the flexible formation of a fused image, which is appropriate for watermark detection. The optimal fused correlator, obtained by combining information from different image components, is derived through a statistical analysis of the correlation detector properties, followed by Lagrange optimization. It is shown that it is preferable to perform detection in a fused image rather than the original image.     

A New Statistical Detector for DWT-Based Additive Image Watermarking Using the Gauss–Hermite Expansion

Traditional statistical detectors of the discrete wavelet transform (DWT)-based image watermarking use probability density functions (PDFs) that show inadequate matching with the empirical PDF of image coefficients in view of the fact that they use a fixed number of parameters. Hence, the decision values obtained from the estimated thresholds of these detectors provide substandard detection performance. In this paper, a new detector is proposed for the DWT-based additive image watermarking, wherein a PDF based on the Gauss–Hermite expansion is used, in view of the fact that this PDF provides a better statistical match to the empirical PDF by utilizing an appropriate number of parameters estimated from higher-order moments of the image coefficients. The decision threshold and the receiver operating characteristics are derived for the proposed detector. Experimental results on test images demonstrate that the proposed watermark detector performs better than other standard detectors such as the Gaussian and generalized Gaussian (GG), in terms of the probabilities of detection and false alarm as well as the efficacy. It is also shown that detection performance of the proposed detector is more robust than the competitive GG detector in the case of compression, additive white Gaussian noise, filtering, or geometric attack.