Rapid blockwise multi-resolution clustering of facial images for intelligent watermarking

Population-based evolutionary computation (EC) is widely used to optimize embedding parameters in intelligent watermarking systems. Candidate solutions generated with these techniques allow finding optimal embedding parameters of all blocks of a cover image. However, using EC techniques for full optimization of a stream of high-resolution grayscale face images is very costly. In this paper, a blockwise multi-resolution clustering (BMRC) framework is proposed to reduce this cost. During training phase, solutions obtained from multi-objective optimization of reference face images are stored in an associative memory. During generalization operations, embedding parameters of an input image are determined by searching for previously stored solutions of similar sub-problems in memory, thereby eliminating the need for full optimization for the whole face image. Solutions for sub-problems correspond to the most common embedding parameters for a cluster of similar blocks in the texture feature space. BMRC identifies candidate block clusters used for embedding watermark bits using the robustness score metric. It measures the texture complexity of image block clusters and can thereby handle watermarks of different lengths. The proposed framework implements a multi-hypothesis approach by storing the optimization solutions according to different clustering resolutions and selecting the optimal resolution at the end of the watermarking process. Experimental results on the PUT face image database show a significant reduction in complexity up to 95.5 % reduction in fitness evaluations compared with reference methods for a stream of 198 face images.     

High-quality blind watermarking in halftones using random toggle approach

This paper presents a blind watermarking method for embedding large data into halftone images. Watermarking in ready-to-print halftones is desirable in printer applications such as authentication and document/image security. It is challenging to embed large information into halftones, while maintaining high image quality. In this paper, we first review a series of halftone watermarking methods that embed data by using Embedding Toggle (ET) in the selected positions. We find that such ET-based methods have two shortcomings: 1) the image quality is limited because of the unknown input data and randomly selected embedding positions, and 2) the selected embedding positions must be recorded to retrieve the hidden data. To tackle the above disadvantages, this study makes two improvements. First, we propose a random toggle approach, in which the embedding positions are movable. Therefore, after the data are embedded, each dot can still be shifted to the most appropriate position to improve the image quality. Second, a self-decodable even/odd parity checking scheme is proposed to embed one bit information in each image block. We also propose a new search strategy, called Swap-Only Block-Based (SOBB) search. By integrating SOBB search with the direct binary search method, the image quality can be greatly improved without damaging the hidden data. From experimental results, the proposed method demonstrated sufficient robustness and excellent image quality.     

Minority codes with improved embedding efficiency for large payloads

Improving embedding efficiency is important for watermarking with large payloads. In this paper, we propose a coding scheme named Minority codes by observing the relationship between the populations and positions of the binary bits in a sequence whose length is an odd number. In such a sequence, there is always a bit value, whose population is minority. We observe that the positions of the minority bit in two complement sequences are the same. By using this property, we create Minority codes whose codebook is composed of a pair of complement sequences for each entry. Minority codes can be combined with watermarking algorithms to improve embedding efficiency, because we can always identify the codeword that causes fewer embedding changes according to the host image and the watermarking method. The performance of Minority codes is analyzed theoretically and supported experimentally. The complexity of Minority codes is quite low and suitable for large payloads.     

Digital watermarking algorithm based on Kalman filtering and image fusion

A digital watermarking algorithm based on Kalman filter and image fusion is proposed. The digital watermarking can be viewed as a process that embedding a weak signal (watermark) to a strong signal (original image), so the process of watermarking can be viewed as a process of image fusion. In the proposed watermarking algorithm, the watermark embedding and extraction process are expressed as the state estimate process, and Kalman filter is used as an optimal estimation algorithm in the process of image fusion. An optimal estimation model is built according to the watermark image and the original image, and then the state equation and the corresponding measurement equation are built. The optimal estimation is archived in case of the minimum estimation error variance. Crossentropy and mutual information are used to evaluate the performance of image fusion. Experimental results show that the proposed algorithm has a good performance in both robustness and invisibility.     

A blind audio watermarking technique based on a parametric quantization index modulation

In this paper, we propose an efficient transform-based blind audio watermarking technique by introducing a parametric quantization index modulation (QIM). Theoretical expressions for the signal to watermark ratio and probability of error are derived and then used in an optimization technique based on the Lagrange multipliers method to find the optimal values for the parameters of the parametric QIM that ensure the imperceptibility while maximizing the robustness under an additive white Gaussian noise (AWGN) attack. Moreover, a fast scheme for the implementation of the proposed watermarking technique is developed and an efficient procedure is suggested to find the interval for the best selection of the watermark embedding positions that provide a good trade-off between the effects of high and low pass filtering attacks. The parameters of the resulting optimal parametric QIM coupled with the embedding positions constitute a highly robust secret key for the proposed watermarking technique. We also carry out several experiments to show the usefulness of the theoretical analysis presented in the paper and compare the proposed technique with other existing QIM-based watermarking techniques by considering known attacks such as AWGN, re-quantization, resampling, low/high pass filtering, amplitude scaling and common lossy compressions.

     

Optimized SVD-based robust watermarking in the fractional Fourier domain

Digital watermarking is one of the most effective methods for protecting multimedia from different kind of threats. It has been used for many purposes, like copyright protection, ownership identification, tamper detection, etc. Many watermarking applications require embedding techniques that provide robustness against common watermarking attacks, like compression, noise, filtering, etc. In this paper, an optimized robust watermarking method is proposed using Fractional Fourier Transform and Singular Value Decomposition. The approach provides a secure way for watermarking through the embedding parameters that are required for the watermark extraction. It is a block-based method, where each watermark bit is embedded in its corresponding image block. First, the transform is applied to each block, and then the singular values are evaluated through which the embedding modification is performed. The optimum fractional powers, of the transform, and the embedding strength factor are evaluated through a Meta-heuristic optimization to optimize the watermark imperceptibility and robustness. The Artificial Bee Colony is used as the Meta-heuristic optimization method. A fitness function is employed, at the optimization process, through which the maximum achievable robustness can be provided without degrading the watermarking quality below a predetermined quality threshold Qth. The effectiveness of the proposed method is demonstrated through a comparison with recent watermarking techniques in terms of the watermarking performance. The watermarking quality and robustness are evaluated for different quality threshold values. Experimental results show that the proposed approach achieves a better quality compared to that of other existing watermarking methods. On the other hand, the robustness is examined against the most common applied attacks. It is noticed that the proposed method can achieve a higher robustness degree when decreasing the quality threshold value.     

Visible watermarking based on importance and just noticeable distortion of image regions

Visible watermarking is the process of embedding data (watermark) into a multimedia object (video/image) such that the embedded watermark is perceptible to a human observer. Many times, visible watermarks occlude important portion of multimedia objects. This paper introduces a visible watermarking algorithm to embed a binary logo watermark at N non-overlapping positions in an image such that important portions of the image are not occluded. The important portions are found through visual saliency computation or available human eye fixation density maps. In the proposed visible watermarking, just noticeable distortion is used to adaptively filter the watermark embedding energy based on the image content. A mathematical model in terms of information-content-weighted-structural-similarity-index and visual importance is proposed to find optimal watermark embedding strength. We tested the algorithm on several color images of different sizes and on several binary watermarks of different sizes and found the results to be very promising as per the requirements in visible watermarking. When compared to the state-of-the-art, we also found that the proposed technique does better in not hiding the details of any test image.     

基于图像内容敏感度分析数字水印算法

现有的数字水印技术大多是通过基于对图像进行纹理分析的统计方法和二级统计信息方法确定嵌入点,缺少针对图像内容、意义以及观察者的喜好来确定嵌入点的算法,给出了数字图像内容敏感度的定义及数学模型,并提出一种基于对数字图像内容敏感度分析的小波包结合SVD奇异值分解的鲁棒数字水印新算法。该算法得到数字水印的不可见性与鲁棒性的最佳折中,并支持水印的盲提取。另外,还给出了一种全新的数字水印评价方法——图像内容敏感加权峰值信噪比（ICSP-PSNR）,该方法可以给出含水印图像基于内容的质量评价。     

An adjustable-purpose image watermarking technique by particle swarm optimization

Imperceptibility, security, capacity, and robustness are among many aspects of image watermarking design. An ideal watermarking system should embed a large amount of information perfectly securely, but with no visible degradation to the host image. Many researchers have geared efforts towards developing specific techniques for variant applications. In this paper, we propose an adjustable-purpose, reversible and fragile watermarking scheme for image watermarking by particle swarm optimization (PSO). In general, given any host image and watermark, our scheme can provide an optimal watermarking solution. First, the content of a host image is analyzed to extract significant regions of interest (ROIs) automatically. The remaining regions of non-interest (RONIs) are collated for embedding watermarks by different amounts of bits determined by PSO to achieve optimal watermarking. The parameters can be adjusted relying upon user’s watermarking purposes. Experimental results show that the proposed technique has accomplished higher capacity and higher PSNR (peak signal-to-noise ratio) watermarking.     

Fragile Watermarking Based on Encoding of the Zeroes of the $z$-Transform

In this paper, a new fragile watermarking method for digital image authentication is proposed based on the zero locations of the $z$-transform. The $z$ -transform domain is a new transform space for fragile watermark embedding. Our watermarking method is designed by exploiting the sensitivity of the positions of the zeroes of the $z$ -transform around the unit circle to any change made on the host image. The watermarking system can localize the portions of a watermarked image that have been tampered with with high accuracy. In addition, the newly proposed scheme is more secure than normal least-significant bits-based fragile watermarking techniques. Experimental results as well as the theoretical analysis demonstrated the fragility and accuracy of the new method.      

基于Tchebichef矩的几何攻击不变性第二代水印算法

提出了一种基于原始图像的Tchebichef矩实现的几何攻击不变性第二代盲水印算法,利用原始图像的Tchebichef矩估计图像可能经历的几何攻击的参数来还原图像,其中,原始图像的Tchebichef矩可作为水印检测器的密钥.水印嵌入过程结合人类视觉系统的特性,且可在任何图像变换域中实现,给出了小波域的一种实现方法.水印检测过程采用独立分量分析技术不仅可以检测到水印而且可以提取水印,实现了真正意义上的盲检测.实验结果表明,该水印算法对于通用水印测试软件Stirmark提供的各种攻击具有很好的鲁棒性.     

基于离散小波变换的QR二维条码防伪技术

基于数字水印的快速响应矩阵（QR）二维条码防伪技术的水印容量低、防伪效果差。为解决该问题,提出QR码二值图像Rand灰度化和背景图灰度化方法,以提高防伪水印容量。QR码二值图像灰度化的程度由灰度化阈值决定,并且可以根据实际应用需要灵活确定。在此基础上,设计基于离散小波变换的QR二维条码防伪水印方案,通过量化函数实现水印的嵌入和检测,利用混沌密钥生成的二维混沌序列控制水印嵌入和检测的位置。实验结果表明,该方案在确保条码信息可识别的条件下,提高了QR码防伪水印的性能。     

结合多级小波系数加权均值和量化的可公开敏感水印

传统水印通常对水印嵌入后掩体视觉质量较为关注,而对水印嵌入环节的安全性较为忽视,一些算法尽管提供了水印加密环节,但位置固定,导致嵌入水印易受攻击,而基于参数化小波的水印敏感性在实际中难以应用。针对以上问题,提出一种结合多级小波系数加权均值和量化的可公开敏感水印。在该算法中,首先将掩体图像的消息摘要算法5(MD5)值、用户密钥和初始参数与Logistic映射绑定,用于对水印加密和嵌入环节的多级小波系数进行随机选择;然后通过联合图像专家组(JPEG)压缩的各级小波系数绝对变化量的算术平均值来估算小波系数权重,调整小波系数加权均值以嵌入水印;最后通过孤立黑点滤除策略来提高水印提取质量。理论和实验表明,所提方法具有较好的明文敏感性和密钥敏感性,嵌入水印后图像峰值信噪比(PSNR)可达到45 dB,即使公开水印嵌入环节,嵌入的水印也难以篡改和提取,同时依然对图像剪裁、白噪声、JPEG压缩、覆盖和涂鸦等常规图像攻击具有鲁棒性。     

基于图像特征的鲁棒性数字水印算法

为了同时实现图像版权保护和图像内容的真伪性鉴定,提出了一种基于数字图像特征的鲁棒性数字水印算法。先利用Hessian变换提取宿主图像的特征区域,并根据每个特征区域内各个像素点的局部方向,将用于版权保护的水印信息嵌入到这些特征区域中。同时,向图像中除特征区域之外的区域嵌入用于图像内容真伪鉴定的脆弱性水印。水印提取过程是水印嵌入的逆过程,在不需要原始图像的情况下实现了版权水印和内容鉴定水印的提取。实验表明,该算法能抵杭大多数的移除攻击等几何篡改,对篡改发生的位置定位效果良好。     

基于四元数傅里叶梅林变换的RST不变彩色图像水印算法

提出一种基于四元数傅里叶梅林变换(QFMT)的RST(旋转、缩放和平移)不变彩色图像水印算法,利用图像的不变质心生成具有平移稳定性的圆形特征区域,对这个圆形区域进行QFMT。利用QFMT幅度谱具有旋转和缩放不变性,在QFMT幅度谱中嵌入水印信息。该算法不仅可以抗RST攻击,大大提升水印的鲁棒性,而且可以把水印嵌入所带来的误差扩散到载体图像的各个颜色分量之中,扩大水印嵌入的容量。实验结果表明,该方法具有较好的抗压缩性,对RST等攻击有良好的鲁棒性。     

基于混沌的图像的数字水印隐藏算法

数字水印技术是进行数字产品版权保护的一种手段。该文提出了一种基于混沌的图像的数字水印隐藏方法。该算法应用混沌系统生成的混沌序列，改变水印的嵌入位置，使得嵌入位置具有随机性，同时综合考虑嵌入水印后的视觉效果，使得像素的改变不会影响图像的不可见性。该方法特征：水印的不可见性好；水印的嵌入和提取过程中需个人的密钥，由于混沌的混沌特性，因此不知该密钥的用户无法正确恢复水印；水印的提取不需要原始图像。计算机仿真结果令人满意。     

基于混沌序列的多重数字图像水印算法

采用一维混沌映射，根据不同的混沌初始条件生成多个互不相关的混沌实值序列，进而得到性能良好的多重数字图像水印信号，有效地解决了多重数字图像水印信号的构造问题．同时采用二维混沌映射将各水印信号置乱，随机均匀地叠加在图像小波变换的中低频系数上，各水印信号的嵌入和提取可以互不干扰，解决了多重数字图像水印的嵌入问题．实验结果表明，该算法对各种常见的攻击均具备了一定的抵抗能力，可有效地解决数字图像产品的多著作权问题．     

RDWT domain statistical watermark detector using FRHFMs magnitudes and bivariate Cauchy-Rayleigh distribution

Imperceptibility, robustness and data payload, which are complimentary to each other, are widely considered as the three main properties vital for any image watermarking systems. It is a challenging work to design a statistical model-based multiplicative watermarking scheme for achieving the tradeoff among three main properties. In this paper, we propose a novel statistical image watermarking scheme by modeling local redundant discrete wavelet transform (RDWT) and fast Radial harmonic Fourier moments (FRHFMs) magnitudes with bivariate Cauchy-Rayleigh distribution. Our image watermarking scheme consists of two parts, namely, embedding and detection. In the embedding process, RDWT is firstly performed on the host image and RDWT highpass subbands are divided into non-overlapping blocks. Then FRHFMs are computed on RDWT coefficient blocks. And finally, the watermark signal is inserted into robust RDWT-FRHFMs magnitudes through a non-linear multiplicative approach. In the detection process, robust local RDWT-FRHFMs magnitudes are firstly modeled by employing bivariate Cauchy-Rayleigh distribution, which can capture accurately both marginal distributions and strong dependencies of local RDWT-FRHFMs magnitudes. Statistical model parameters are then estimated effectively by the method of logarithmic cumulants (MoLC) approach. And finally, an image watermark detector for multiplicative watermarking is developed using bivariate Cauchy-Rayleigh model and locally most powerful (LMP) test. Also, we utilize the bivariate Cauchy-Rayleigh model to derive the closed-form expressions for the watermark detector. After performance testing and comparison with the experimental results of existing methods, the proposed statistical image watermarking method has achieved relatively ideal results in terms of robustness, imperceptibility and data payload.

     

Perceptual Digital Watermarking for Image Authentication in Electronic Commerce

Digital watermarking has been presented to protect the copyright of electronic multimedia data. The previous proposed watermarking algorithms mostly embed sequences of random numbers or binary images as the watermarks. In this paper, an image accreditation technique by embedding digital gray-level image watermarks in images is proposed. In the proposed method, the host image and the watermark are decomposed into wavelet coefficients. The contextual energies of the host-image wavelet coefficients are computed to select embedding coefficients. The watermark wavelet coefficients are sorted and then embedded in the selected host coefficients. The experiments show that the proposed method provides extra robustness against JPEG-compression, image-processing, and even composite attacks compared to the traditional embedding methods. Moreover, the proposed method has no need of the original image to extract the embedded watermarks. The proposed method facilitates electronic commerce application developers to select adequate digital watermarking techniques for their development systems.     

基于多数字基整数和小波域JND的多重数字水印

提出了一种新颖的在小波变换域中嵌入多重数字水印的算法。该算法通过利用人眼的视觉特性，计算小波域临界可见误差JND门限，选择加载水印信息的小波系数和控制加载的水印强度。通过引入多数字基整数系统，选择舍适的JND门限作为该系统的基底，将水印的小波系数表示为多数字基整数，最后转化为修改一组宿主图像的小波系数的幅值，从而实现水印嵌入算法．实验结果表明，该算法实现的数字水印对于图像压缩、图像剪切等常见图像处理有很好的鲁棒性。