Jointly Verifying Ownership of an Image Using Digital Watermarking

The current image watermarking schemes only involve one key, thus can not resolve the problem of joint ownership. This paper proposes two totally new algorithms that make use of a secret sharing scheme in cryptography to address this problem. The first one applies Shamir's (2,2) threshold scheme to the watermarking algorithm. A watermark, which is a gaussian distributed random vector determined by two keys, is embedded to selected coefficients in all middle bands in the wavelet domain of an image, so that only when the two keys are put together can the ownership be verified. The second algorithm is a modification of the first one. Three random watermarks are embedded to middle bands in the wavelet domain of an image. For the watermark detection, two thresholds are set, so the watermark detector can verify partial ownership as well as full ownership. Experimental results show that both algorithms have the desired properties such as invisibility, reliable detection and robustness against a wide range of imaging processing operations.     

小波域视觉密码零水印算法

目的传统零水印算法需要构造包含图像特征的水印数据,这样构造的水印往往是无意义的。在已有视觉密码鲁棒水印算法基础上,结合零水印思想,提出小波域视觉密码零水印算法。方法零水印不仅仅是由载体图像生成的,而是其与水印信息共同制造的视觉秘密图份。算法产生2幅图份:主图份(图像特征信息)和所有权图份(零水印)。首先,将载体图像通过合理置乱,去除像素相关性;其次,对置乱后的图像做小波变换,再将小波低频子带分块并对各块做奇异值分解,通过比较块特征值与块特征值均值生成过渡矩阵;然后,将生成的过渡矩阵结合2×2视觉秘密图份算法生成主图份;最后,结合主图份和秘密水印信息产生所有权图份,同时将其保存到认证中心。结果针对零水印信息不够直观,在不对载体进行任何改动的情况下,将有意义二值图像作为零水印嵌入到载体图像中去。即使在很强的鲁棒干扰环境中,本文方法仍然比传统的零水印算法表现出色。结论提出了一种可靠的图像版权认证零水印算法。实验结果表明,算法具有良好的安全性,同时对多种图像处理具有很好的鲁棒性。     

An ASIC based invisible watermarking of grayscale images using pixel value search algorithm (PVSA)

Digital image watermarking has become more popular due to its applications in copyright protection and secret communication. Most of the image watermarking algorithms reported till date involve modification of the host contents for embedding a secret data, leading to a reduced robustness and a limited embedding capacity. In the present work, a novel spatial domain watermarking scheme called Pixel Value Search Algorithm (PVSA) is proposed using a linear search operation to achieve high robustness and a theoretically unlimited embedding capacity. In the proposed scheme, secret data are embedded into a host image by mapping their intensity values into row and column locations. Due to this linear mapping of secret data, the host structural content is not altered. In addition, multiple watermarks can be mapped into a single host image using the PVSA technique. The proposed algorithm is verified using MATLAB^® simulations and its performance characteristics are assessed using a standard benchmark tool called strimark. Experimental results illustrate the robustness of the PVSA technique against the attacks of Gaussian blurring, Gaussian noise, salt and pepper noise, Poisson noise, speckle noise, mean and median filtering, histogram equalization, image sharpening, intensity transformation, unsharp filtering, JPEG attack, etc. Subsequently an ASIC implementation of the PVSA algorithm is carried out using Verilog HDL and various modules of the Cadence^® EDA tool so as to integrate the chip as a watermark co-processor. The ASIC implementation using a 0.18 μm technology at an operating frequency of 100 MHz consumes a power of 326.34 μW for the complete hardware architecture.

     

面向神经辐射场的水印算法

针对隐式表示的3D模型的版权保护问题,提出了一种面向神经辐射场（NeRF）的水印算法。该算法通过嵌入网络对训练集中的图像嵌入水印,再利用NeRF模型进行3D模型建模。版权验证方通过给定一个秘密视角作为神经辐射场的输入,生成新视角下的图像作为后门图像,接着利用神经网络的过参数化方法设计一个水印提取器,获取该视角下嵌入的水印图像。在黑盒场景下,一旦怀疑3D模型被未经授权的使用,验证方则可以通过秘密视角提取水印以验证网络版权。实验结果表明,所提算法提取水印不仅具有良好的视觉效果,而且对不同类型的噪声攻击具有较好的抵抗能力。     

可视密码学的Contourlet域图像水印

将可视密码学引入到水印的预处理中,提出了一种Contourlet域的安全性较高的图像水印算法。该算法首先根据可视密码理论将水印信息隐藏到一定数目的图片中,选取其中任一图片作为水印,然后对载体图像进行分块,通过聚类找出适合嵌入水印的块,并进行Contourlet变换,在变换系数的最大奇异值上嵌入水印。水印提取时只需用特定数目的图片对提取出的信息进行叠加,其过程无需大量计算和密码学知识。实验表明,该算法还具有抵抗噪声、滤波、JPEG压缩等常规攻击和抗剪裁等功能。     

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。     

基于线性空间隐藏模型的可逆图像水印算法

提出一种基于线性空间隐藏模型的可逆图像水印算法.通 过对原始图像载体互不重叠的划分形成图像块序列,对其进行整数小波变换,获取待嵌水印子带.根据0/1水印序列和线性空间隐藏模型,将水印不可感知地嵌入到图像的小波域中,提高水印鲁棒性和不可见性. 只需判断奇偶性提取水印,并且通过简单逆向平移恢复原始.线性空间隐藏模型的提出实现了水印间相互独立,从而 使该算法能扩展到多著作权的无损水印领域.投票原则的使用又进一步提高水印的 鲁棒性和降低了误检率.在无外界干扰的条件下,拥有密 钥和其他秘密参数的用户能够无损恢复原始图像.仿真实验表明,与相关工作比较该算 法能应对一定程度的有损压缩和高斯噪声攻击,表现出 较高的鲁棒性、安全性和不可见性.     

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.     

A (2, 2) Visual Cryptography Technique with Improved Contrast

ABSTRACT

Visual cryptography is a technique used to share a secret among many participants. The problem with visual cryptography technique is that the secret is not perfectly recovered, i.e. a black secret pixel is perfectly recovered but a white secret pixel is recovered with less contrast. Because of this, the overall quality of recovered secret is poor. So to improve the quality of recovered secret image, we need to improve the contrast. In this paper, we have proposed a (2, 2) visual cryptography technique with improved contrast as compared to the traditional (2, 2) visual cryptography scheme (VCS). In the proposed technique, we have used additional basis matrices for encrypting the secret pixels. The quality of the recovered secret image is compared with traditional (2, 2) VCS using various image quality metrics.     

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。     

Halftone Visual Cryptography Via Error Diffusion

Halftone visual cryptography (HVC) enlarges the area of visual cryptography by the addition of digital halftoning techniques. In particular, in visual secret sharing schemes, a secret image can be encoded into halftone shares taking meaningful visual information. In this paper, HVC construction methods based on error diffusion are proposed. The secret image is concurrently embedded into binary valued shares while these shares are halftoned by error diffusion—the workhorse standard of halftoning algorithms. Error diffusion has low complexity and provides halftone shares with good image quality. A reconstructed secret image, obtained by stacking qualified shares together, does not suffer from cross interference of share images. Factors affecting the share image quality and the contrast of the reconstructed image are discussed. Simulation results show several illustrative examples.      

A contextual based double watermarking of PET images by patient ID and ECG signal

This paper presents a novel digital watermarking framework using electrocardiograph (ECG) and demographic text data as double watermarks. It protects patient medical information and prevents mismatching diagnostic information. The watermarks are embedded in selected texture regions of a PET image using multi-resolution wavelet decomposition. Experimental results show that modifications in these locations are visually imperceptible. The robustness of the watermarks is verified through measurement of peak signal to noise ratio (PSNR), cross-correlation (CC%), structural similarity measure (SSIM) and universal image quality index (UIQI). Their robustness is also computed using pixel-based metrics and human visual system metrics. Additionally, beta factor (β) as an edge preservation measure is used for degradation evaluation of the image boundaries throughout the watermarked PET image. Assessment of the extracted watermarks shows watermarking robustness to common attacks such as embedded zero-tree wavelet (EZW) compression and median filtering.     

小波变换域图像水印嵌入对策和算法

稳健性是图像隐形水印最基本的要求之一.嵌入对策、嵌入公式、嵌入强度都影响水印的稳健性.提出了一个基于离散小波变换(DWT)的新的隐形水印嵌入对策.根据小波图像系数的分布特点和对小波系数振幅的定性、定量分析,水印应当首先嵌入小波图像低频系数,若有剩余,再按小波图像频带重要性的排序嵌入高频带.同时指出,水印嵌入到小波图像低频系数和高频系数需要用不同的嵌入公式.应用该嵌入对策,提出了一种把视觉系统掩蔽特性结合到水印编码过程中的自适应水印算法:将小波系数组织成小波块,采用一种新的方法将小波块分类,并根据分类的结果     

基于直方图重复嵌入水印的算法研究

针对空域图像水印算法抗干扰能力差的缺陷,提出一种基于直方图重复嵌入水印的空间域水印算法。利用直方图统计不同灰度级像素数量的方法,选择将二值水印图像嵌入到载体图像灰度级较低和较高的区域,使图像能够适应不同情况下的图像处理攻击,并把所选择的区域作为提取水印的密钥,提高水印的安全性。为了说明算法的有效性,分别模拟噪声、低通滤波、剪切、JPEG压缩、锐化处理等攻击情况提取水印,实验结果表明,该算法能够对付这些常见的图像处理和攻击,具有很好的鲁棒性。     

A novel two-in-one image secret sharing scheme based on perfect black visual cryptography

Perfect black visual cryptography scheme (PBVCS) shares a binary secret image into n shadows. Stacking any \(k(k<n)\) shadows can reveal a vague secret image, and the black area of the secret image is recovered as perfect black. Two-in-one image secret sharing (TiOISS) scheme is a secret image sharing method with two decoding options. It can not only decode a vague secret image by stacking any k shadows, but also reveal the original grayscale secret image with k shadows by computation. Researchers proposed some TiOISS schemes, which are based on visual cryptography and polynomial-based image secret sharing (PISS). Since PISS reveals the secret image by Lagrange’s interpolation, these TiOISS schemes need complex computation. In this paper, we proposed a novel TiOISS scheme based on PBVCS using exclusive OR operation. Compared with literature TiOISS schemes, our scheme does not need complex computation in revealing process, and it can be used in real-time application. The grayscale secret image can be recovered quickly with a few Boolean operations.     

灰度图像水印的自适应二维数字水印算法

本文提出了一种采用可视灰度图像作为水印信号,根据人类视觉掩体特性进行分类,并结合系数自身的特点,通过修改DCT域中低频和次低频系数来嵌入不同强度水印的算法。实验结果表明,应用所提出的算法实现的水印对常见图像处理和噪声干扰具有很好的稳健性。     

Visual cryptographic techniques for secret image sharing: a review

ABSTRACT

A visual cryptography scheme (VCS) allows one to decrypt images without any knowledge of cryptography and computational efforts. VCS allows secret image sharing such that we can divide the original image into meaningful or nonmeaningful shares. The shares are distributed among participants; during decryption, the original secret image is recovered through stacking all or some of the shares by the human visual system. Various techniques of visual cryptography were constructed mainly for binary images but later, they were enhanced to handle gray-scale or color images. This article focuses on the study of various visual cryptographic schemes and analyses the performance on the basis of various parameters such as, pixel expansion, type of shares generated, image format, number of secret images, encryption method, etc.. In the proposed work, we give a precise and complete review of various visual cryptographic schemes based on different research works related to this area and cite the relevant literature.     

A multimodal biometric watermarking system for digital images in redundant discrete wavelet transform

The traditional watermarking algorithms prove the rightful ownership via embedding of independent watermarks like copyright logos, random noise sequences, text etc into the cover images. Coupling biometrics with watermarking evolved as new and secure approach as it embeds user specific biometric traits and thus, narrows down the vulnerability to impostor attacks. A multimodal biometric watermarking system has been proposed in this paper in the redundant discrete wavelet transform(RDWT). Two biometric traits of the user i.e. the iris and facial features are embedded independently into the sub-bands of the RDWT of cover image taking advantage of its translation invariant property and sufficient embedding capacity. The ownership verification accuracy of the proposed system is tested based on the individual biometric traits as well as the fused trait. The accuracy was enhanced while using the fused score for evaluation. The security of the scheme is strengthened with usage of non-linear chaotic maps, randomization via Hessenberg decomposition, Arnold scrambling and multiple secret keys. The robustness of the scheme has been tested against various attacks and the verification accuracy evaluated based on false acceptance rate, false rejection rate, area under curve and equal error rate to validate the efficacy of the proposed scheme.

     

VPVC: verifiable progressive visual cryptography

In traditional k-out-of-n visual cryptography (VC), a secret image is visually decoded only if a subset of k or more shares are stacked together else nothing will be revealed. Progressive visual cryptography (PVC) scheme differs from the traditional VC where clarity and contrast of the decoded secret image are increased progressively with the number of stacked shares. Shares are most sensible objects since they carry secret; hence, verifying the reliability and authenticity of all shares before decoding the secret image prevents a participant from intentionally or unintentionally providing invalid data. This paper proposes a novel verifiable progressive visual cryptography approach with additional embedding capacity in each share which is used for self-embedding authentication data, copyright information along with confidential payload. These embedded informations in a share can be retrieved and verified at the time of any conflict. Proposed approach also eliminates many unnecessary encryption constraints of VC like pixel expansion, noise-like shares, explicit requirement of codebook and restriction on number of participants. Experiments show that in spite of having various credentials of participants, embedded in shares, the contrast of the decoded secret image remains 50 % without reducing the level of secrecy. By experiments, it is also confirmed that proposed approach can effectively localize the tampered region of the share.     

Video Identification Based on Watermarking Schemes and Visual Cryptography

Related to the growth of data sharing on the Internet and the wide - spread use of digital media, multimedia security and copyright protection have become of broad interest. Visual cryptography () is a method of sharing a secret image between a group of participants, where certain groups of participants are defined as qualified and may combine their share of the image to obtain the original, and certain other groups are defined as prohibited, and even if they combine knowledge of their parts, they can’t obtain any information on the secret image. The visual cryptography is one of the techniques which used to transmit the secrete image under the cover picture. Human vision systems are connected to visual cryptography. The black and white image was originally used as a hidden image. In order to achieve the owner’s copy right security based on visual cryptography, a watermarking algorithm is presented. We suggest an approach in this paper to hide multiple images in video by meaningful shares using one binary share. With a common share, which we refer to as a smart key, we can decrypt several images simultaneously. Depending on a given share, the smart key decrypts several hidden images. The smart key is printed on transparency and the shares are involved in video and decryption is performed by physically superimposing the transparency on the video. Using binary, grayscale, and color images, we test the proposed method.