利用综合特征提取的数字图像版权保护算法

为了有效地保护和验证数字媒体作品的版权信息,提出一种区别于传统嵌入式鲁棒水印的数字水印算法.算法中所提取的特征是由区域亮度和纹理特性所组成的综合特征,其中亮度特征的提取利用了扩展盒中脑神经网络(gBSB)的聚类功能,对于区域的纹理特征,则是通过分析其直方图统计矩来提取的.仿真结果表明,该水印方案对于常规的信号处理及几何变换攻击具有良好的鲁棒性,是一种实用的、有效的数字图像版权保护水印算法.     

基于奇偶量化的彩色图像盲水印算法

提出一种基于奇偶量化的彩色图像小波域的数字水印算法。首先对水印图像进行置乱处理,然后对图像进行翻转,最后利用混沌系统产生的混沌序列对水印进行加密。水印嵌入时,采用小波变换并利用奇偶量化规则将加密后的水印嵌入到载体图像蓝色分量最深层的四个子带中。水印提取时,不需要原始图像的参与,实现了盲提取。仿真实验和性能分析表明,该算法有很好的不可见性和鲁棒性,可以有效地抵抗JPEG压缩、噪声、剪切等攻击。     

Fidelity-guaranteed robustness enhancement of blind-detection watermarking schemes

Watermarking performance enhancement has always been a difficult task since the performance metrics of watermarking systems, i.e., fidelity, robustness, and payload size, inherently conflict with each other. Nowadays, most watermarking schemes hide payloads according to predefined rules or empirical perceptual models. Therefore, the performance of digital watermarking schemes can be determined only passively. In this study, a genetic algorithm-based framework for watermarking performance enhancement is proposed. Watermarked results having better robustness, guaranteed fidelity, and fixed payload size can be obtained. Existing blind-detection watermarking schemes can be improved significantly by incorporating the proposed framework. In addition, the proposed framework has many desirable advantages such as asymmetric embedding/detection overhead, easy integration with existing data-hiding schemes, and direct control over fidelity and robustness.     

Hardware assisted watermarking for multimedia

Digital media offer several distinct advantages over analog media, such as high quality, ease of editing, and ease of processing operations such as compression and high fidelity copying. Digital data is commonly available through digital TV broadcast, CD, DVD, and computing devices such as personal computers. The ease by which a digital media object can be duplicated and distributed has led to the need for effective digital rights management tools. Digital watermarking is one such tool. Watermarking is the process of embedding extra data called a watermark into a multimedia object, like image, audio, or video, such that the watermark can later be detected or extracted in order to make an assertion regarding the object. During the last decade, numerous software based watermarking schemes have appeared in the literature and watermarking research has attained a certain degree of maturity. But hardware based watermarking systems have evolved more recently only and they are still at their infancy. The goal of hardware assisted watermarking is to achieve low power usage, real-time performance, reliability, and ease of integration with existing consumer electronic devices. In this paper, we survey the hardware assisted solutions proposed in the literature for watermarking of multimedia objects. The survey is preceded by an introduction to the background issues involved in digital watermarking.     

基于离散分数傅里叶变换的SVG数字水印技术

提出了一种基于离散分数傅里叶变换(DFRFT)的SVG图形水印算法,用于SVG的版权保护.将水印嵌入到SVG图形控制点坐标构造的复数信号的离散分数傅里叶变换频谱中.经实验结果验证,该算法具有较强的透明性,对于通常的图形几何变换以及局部修改攻击,均有令人满意的鲁棒性.     

基于图像块等级模型的多重认证水印算法

提出了一种新的用于灵活图像认证的多重水印嵌入算法.不同于传统的块独立水印算法中每个图像块只嵌入一个水印信息,算法对每个图像块嵌入多重水印信息.提出了两个通用的图像块等级模型,形成图像块内部的等级结构,对每个图像块以及图像块内部的各等级子块进行独立的水印生成和嵌入.将图像特征值映射为混沌系统的初值,并将图像块的编号映射为混沌系统的迭代次数,经过混沌迭代生成图像块水印,再将水印信号替代图像块中选定像素点的最低有效位,完成水印的嵌入.实验结果表明,该算法可对图像进行多重认证,对篡改区域进行精确的检测与定位,并能选择不同的定位精度.     

基于DWT-DCT和Zernike矩的灰度级鲁棒性水印算法

鲁棒性是数字水印极为重要的指标.目前大多数文献中的鲁棒性水印方案对常规信号处理攻击均具有良好的鲁棒性,但抗几何攻击的鲁棒性相对较弱.提出了一种新的灰度级鲁棒性水印算法,对常规信号处理攻击和几何攻击均具有良好的鲁棒性.水印算法的鲁棒性由以下3方面获得:1)选择载体图像的内切圆盘作为Zernike矩的计算域,选择内切圆盘的内接正方形作为水印的嵌入区域.2)在载体图像嵌入区域的层叠DWT-DCT域嵌入水印,获得对常规信号处理攻击的强鲁棒性.3)保存原始含水印图像的2个Zernike矩作为校正几何攻击的参数,获得抗几何攻击能力.实验结果表明,该水印算法嵌入容量大,不仅对大角度旋转和大尺度缩放等几何攻击具有很好的鲁棒性,而且可以有效地抵抗有损压缩和常规信号处理攻击.     

基于改进曲率尺度空间技术的图像水印算法

提出一种新的鲁棒性水印算法,利用改进的曲率尺度空间技术,提取图像的少量较顽强角点,用于重建受几何攻击的图像。选取2个chirp信号作为水印信息,将其嵌入图像的分数傅里叶变换（FRFT）域,选用变换阶次和水印嵌入位置矩阵作为算法密钥,根据chirp信号在FRFT域呈现的冲激特征检测水印信号。仿真实验结果表明,该算法具有较高不可见性、安全性和鲁棒性。     

基于Zernike矩和DCT变换的数字水印算法

提出一种基于Zernike矩和DCT变换的鲁棒数字水印算法,对图像的旋转角度进行估计,以提高其抵抗旋转攻击的能力,将基于图像内容的具有正交特性的Zemike多项式作为水印信号,并在Watson视觉感知模型的控制下嵌入图像低频系数中,同时采用相关检测方法确定水印的存在,实验结果表明,该算法具有良好的鲁棒性、不可见性及可检测性。     

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。