Image Copyright Research Articles

A new watermark decoder in DNST domain using singular values and gaussian-cauchy mixture-based vector HMT

There are three indispensable, yet contrasting requirements for a watermarking scheme: imperceptibility, robustness, and payload. Therefore, it is a challenge to obtain a tradeoff among above requirements in image watermark detection. In this paper, we propose a new statistical watermark decoder in discrete non-separable Shearlet transform (DNST) domain using singular values and Gaussian-Cauchy mixture-based vector hidden Markov tree (HMT). Our method can obtain great performance in imperceptibility, robustness and payload, and it is necessary for image copyright protection. We first perform DNST on the host image, and apply singular value decomposition (SVD) to the significant DNST domain high entropy blocks. We then embed the digital watermark into the DNST high entropy blocks by modifying the robust singular values. At the receiver, by combining the Gaussian-Cauchy mixture-based vector HMT and maximum likelihood (ML) decision, we propose a new blind image watermark decoder in DNST domain. Here, robust DNST domain singular values are firstly modeled by using Gaussian-Cauchy mixture-based vector HMT, where the Gaussian-Cauchy mixture marginal distribution and various strong dependencies of DNST domain singular values are incorporated. Then the statistical model parameters of Gaussian-Cauchy mixture-based vector HMT are estimated using parameter-expanded expectation–maximization (PXEM) approach. And finally, a blind image watermark decoder is developed using Gaussian-Cauchy mixture-based vector HMT and ML decision rule. The major contribution of this paper is the use of singular value, Gaussian-Cauchy mixture-based vector HMT and PXEM algorithms, which enhances the performance of watermarking scheme. Experimental results on some test images and comparison with well-known existing methods demonstrate the efficacy and superiority of the proposed method.

Combining polar harmonic transforms and 2D compound chaotic map for distinguishable and robust color image zero-watermarking algorithm

Although zero-watermarking can provide an effective and distortion-free scheme for image copyright protection, its robustness and discriminability do not meet expectations in existing methods. Some cannot resist effectively geometric attacks, others do not consider the discriminability and equalization. For that reason, this paper proposes a robust and distinguishable color image zero-watermarking algorithm based on polar harmonic transforms (PHTs) and compound chaotic map. In the proposed algorithm, firstly three PHTs moments of an image are computed simultaneously and accurate moments are selected for the robustness. Then, content-based binary feature sequence is acquired by judging the relation between magnitudes of adjacent moments for the discriminability. Finally, compound chaotic map is employed to encrypt copyright logo for ensuring security and scramble binary feature sequence for improving the equalization. Experimental results show that the proposed zero-watermarking algorithm has good equalization and discriminability, and an advantage in robustness compared with other zero-watermarking and traditional watermarking.

Wavelet transform modulus maxima‐based robust logo watermarking

Digital image watermarking is used to protect the copyright of digital images. In this study, a novel blind logo image watermarking technique for RGB images is proposed. The proposed technique exploits the error correction capabilities of the human visual system. It embeds two different watermarks in the wavelet/multiwavelet domains. The two watermarks are embedded in different sub-bands, are orthogonal, and serve different purposes. One is a high capacity multi-bit watermark used to embed the logo, and the other is a 1-bit watermark which is used for the detection and reversal of geometrical attacks. The two watermarks are both embedded using a spread spectrum approach, based on a pseudo-random noise sequence and a unique secret key. Robustness against geometric attacks such as rotation, scaling, and translation (RST) is achieved by embedding the 1-bit watermark in the wavelet transform modulus maximacoefficients of the wavelet transform. The experimental results show that the proposed watermarking technique has better distortion parameter detection capabilities and compares favourably against existing techniques in terms of robustness against geometrical attacks such as RST.

Real-time attacks on robust watermarking tools in the wild by CNN

Robust watermarking is a widely used technology to protect image copyright. Robustness, the ability to resist various distortions, is the most important property of robust watermarking algorithm. So to improve the robustness of the watermarking schemes, watermark attacking algorithms also attract much attention. Far from now, the existing watermarking attack methods cannot well balance the removal ability and visual quality. To address this issue, this paper proposed a removal attack by a convolutional neural network (CNN). Considering the speed requirements of real-time attack applications, for short computing time, we use a simple but powerful CNN. According to the amount of knowledge of watermarking, a corresponding dataset of watermark images is constructed. After that, the CNN model is trained to remove watermark with these datasets. The experiments show that the trained model can not only effectively remove the watermark, but also recover the original image without much image quality degradation.

An improved robust image watermarking by using different embedding strengths

Image watermarking technique is an alternative solution to protecting digital image copyright. This paper proposed a new embedding technique based on different embedding strengths for embedding a watermark. An image is divided into non-overlapping blocks of 8 × 8 pixels. The variance pixel value was computed for each image block. Image blocks with the highest variance value were selected for the embedding regions. Therefore, it was transformed by discrete cosine transforms (DCT). Five DCT coefficients in the middle frequency were selected and the average of selected DCT blocks was calculated to generate different embedding strengths by using a set of rules. The watermark bits were embedded by using a set of embedding rules with the proposed different embedding strengths. For an additional security, the binary watermark was scrambled by using an Arnold Transform before it was embedded. The experimental results showed that the proposed scheme achieved a higher imperceptibility than the other existing schemes. The proposed scheme achieved a watermarked image quality with a PSNR value of 46 dB. The proposed scheme also produced a high watermark extracting resistance under various attacks.

A robust zero-watermarking algorithm for color image based on tensor mode expansion

Digital zero-watermarking technology is an effective measure to protect image copyright, and many algorithms have been proposed based on zero-watermark. However, most of the existing zero-watermarking algorithms are designed for grayscale images. In this paper, a new zero-watermarking algorithm for color image based on tensor mode expansion is proposed. In the proposed scheme, four images of R, G, B, and gray are firstly generated from the original image. Then, the four images are appropriately combined to construct two three-dimensional tensors, and tensor expansion is performed on the obtained tensors. By performing singular value decomposition (SVD) and discrete cosine transform (DCT) on the expanded data, a feature image containing the main information of the host image can be generated. Finally, the feature image is fused with the specified logo image to obtain a zero-watermark image. Experimental results show that the proposed algorithm is robust to noise attacks and common image processing attacks, and better performances compared with some existing algorithms are also achieved. In addition, since the proposed algorithm is based on color images, it can make full use of all aspects of color images.

NSCT-Based Robust and Perceptual Watermarking for DIBR 3D Images

Depth-image-based rendering (DIBR), where arbitrary views are synthesized from a center image and depth image, has received much attention in the three-dimensional (3D) research field. With advances in depth-acquisition techniques and the proliferation of 3D glasses and 3D display devices, there is a growing demand for schemes to protect the copyrights of DIBR 3D images. Digital watermarking is a typical protection technology and designing a watermarking method for DIBR 3D images is a challenging task because the synchronization of watermarks can easily be broken in the process of generating synthetic images. To address this issue, we propose a non-subsampled contourlet transform (NSCT)-based blind watermarking for DIBR 3D images. To ensure the proposed method has properties of robustness against the DIBR process, we conduct an analysis of robustness for NSCT subbands against DIBR attacks. Based on the analysis results, we select subbands that are robust against DIBR attacks and embed watermark in the low coefficients of NSCT subbands using quantization-based embedding. While ensuring robustness, the proposed method also improves the imperceptibility of watermarks by adjusting their embedding strength according to computed perceptual masking values. Through experiments, we show that the proposed method is robust against both desynchronization attacks of the DIBR process and common attacks including signal processing operations and geometric distortions. The high imperceptibility of our method is also verified by several evaluation metrics in a subjective and objective manner.

A novel watermarking algorithm based on characteristics model of local fragmentary images

Watermarking is a popular technology to protect the copyright of digital image from illegal infringement. Traditional watermarking algorithms cannot better resist the illegal tampering attacks, causing serious security issues. This paper aims to propose an image watermarking algorithm with ability against illegal tampering attacks. The original image should be firstly pre-processed, and its fragmentary characteristic function of local image block is used to generate watermark locations randomly. When the watermark is illegally tampered and damaged, the generated fragmentary characteristic factor can be used to re-construct the original image. Finally, the forensics of original image is realised. The experimental results show that the proposed algorithm can effectively embed a watermark into image. Besides, the original image can be restored even if the watermark is damaged. It is also robust to the typical attacks and has ability against tampering over a large area of the image.

Robust Dual-Color Watermarking Based on Quaternion Singular Value Decomposition

This paper proposes a robust dual-color watermarking based on quaternion singular value decomposition (QSVD), which can embed large payloads into color images with low distortion, and can obtain strong robustness to process color image in a holistic manner. First, two notes are proposed for designing the proposed watermarking scheme, one of which is about three strong correlations found in <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$U$ </tex-math></inline-formula> that can be used for watermark embedding, and the other is analyzing the feasibility of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$V$ </tex-math></inline-formula> compensation for QSVD-based watermarking scheme. In addition, a fast structure-preserving algorithm is used to calculate the singular value decomposition (SVD) of a quaternion matrix, which makes the procedure computationally more flexible and efficient. Then a new watermarking scheme is proposed to protect the copyright of color images. This scheme uses quaternion to make the color image channels correlated so that the proposed watermarking scheme has strong anti-attack performance. Experimental results show that the proposed dual-color watermarking is not only imperceptible but also robust to some common attacks, and the performance of the proposed method outperforms other methods considered in this work.

JND-Guided Perceptually Color Image Watermarking in Spatial Domain

Watermarking is an effective solution for copyright protection and forensics tracking via hiding information into the image signal. Recently, spatial-embedding watermarking methods from different transform domain have been proposed rapidly and effectively protect the copyright of the color image. Compared to the individual frequency domain method, it has both advantages of spatial domain and frequency domain. Here, we proposed a novel spatial-embedding watermarking method based on an attended just noticeable difference (JND) model with color complexity, to achieve a good tradeoff between robustness and perceptual quality. In particular, at the spatial embedding level, the direct current (DC) coefficients are selected for embedding and the perceptual JND model is used to guide the amount of pixel modification to improve visual quality. Different from the previous JND model, we proposed an attended JND model that considers color complexity, which is more consistent of the human visual perception model. Compared with the other JND models, the proposed JND model is more suitable for the watermarking framework. Experimental results show that the proposed watermarking scheme has better performance than other existing watermarking schemes. This greatly benefits the practical implementations of the spatial-embedding watermarking methods.

Blind Image Watermark Decoder in UDTCWT Domain Using Weibull Mixtures-Based Vector HMT

As one promising solution, digital watermarking has been proposed to resolve image copyright protection and content authentication, and has been applied successfully in many fields. Owing to their excellent description capability and invariance property, statistical models have become a popular tool for the image watermarking resulting in favorable trade-offs among imperceptibility, robustness and data payload. By modeling the robust undecimated dual tree complex Wavelet transform (UDTCWT) coefficient magnitudes with the Weibull mixtures based vector hidden Markov trees (HMT) and employing maximum likelihood (ML) test criterion, we propose a new image watermarking approach in UDTCWT domain in this paper. Our image watermarking approach consists of two parts, namely, embedding and extracting. In the embedding process, we compute the robust UDTCWT coefficient magnitudes with UDTCWT domain real/imaginary parts, and insert the digital watermark into the significant UDTCWT coefficient magnitude subband. In the extracting phase, robust UDTCWT coefficient magnitudes are firstly modeled by employing the Weibull mixture-based vector HMT, where the statistical properties of UDTCWT magnitudes are captured accurately. Then the expectation/conditional maximization (ECM) approach is introduced to estimate the statistical model parameters. Finally, an image watermark decoder for multiplicative watermarking is developed using the Weibull mixtures based vector HMT and ML test. The experiments show that the proposed method not only improves the imperceptibility, but also increases the robustness performance and outperforms state-of-the-art methods on a set of standard test images.

Development of a Watermark Embedding Algorithm within Digital Images in Frequency Domain using Ant colony Algorithm

In this paper, an algorithm of watermark embedding within digital cover images was developed, in order to guarantee the copyright of digital images. The proposed algorithm depends transform the image to frequency domain, and ant colony algorithm to determine the optimal blocks to execute the embedding process. Many factors affects the achievement of watermark requirement, the most important factors are embedding domain, embedding method, coefficient used for embedding and blocks locations where The optimal location of them, that varies depending on the nature of the image and the attacks. First, we divided the cover image into 8*8 blocks and calculating standard deviation between their pixels to detect blocks of pixels with strong edges, which is considered the best in the embedding process due to its robustness towards the attacks. Then we used DCT (Discrete cosine transform) on blocks to transfer the original cover image to frequency domain and execute the embedding process relying on the proposed algorithm in two coefficients that belong to the medium frequency of the specific blocks from ants algorithm which provides flexibility in determined the most important blocks in terms of balancing between robust of watermark and transparency of the watermark image. The proposed algorithm provided good results in the watermark robustness and transparency in proportion to the nature of cover image towards various types of image processing.

A blind color image watermarking scheme with variable steps based on Schur decomposition

The widespread application of the Internet makes the protection of image copyright face serious challenges. For resolving this problem, this paper designs a blind color digital image watermarking algorithm which meets the requirements of invisibility, security and robustness. The advantages of the proposed method include the following two points: 1) the proposed method uses Affine transformation with large key space to encrypt the watermark information; 2) Schur decomposition with low complexity is selected and performed on the matrix blocks in different color channels of the host image. In this proposed method, the watermark embedding and blind extraction are completed by quantizing the eigenvalues on the diagonal of the decomposed matrix with different quantization steps. Experimental results show that the proposed method not only has good invisibility, but also has high security and strong robustness.

Dual Watermarking for Color Images: A New Image Copyright Protection Model based on the Fusion of Successive and Segmented Watermarking

Watermarking has been suggested as a generic technique to solve various problems associated with topics in the areas of digital rights management and multimedia security. Most of the early methods were based on single watermark embedding, but there are great limitations when single watermark embedding algorithms are tried into practical applications. The multiple watermarks are intended to convey different information at the same time. Current approaches rely on adding many watermarks in different bands or channels by means of scaling factor and embedding locations that are mainly defined by experts. This brought many challenges in achieving equilibrium between security, robustness, and quality. The aim of this work is to introduce an intelligent dual watermarking model for colour images that ensure image security for copyright protection (dual watermarking for single purpose). To optimize the dual watermarking requirements, the proposed model that employs both successive (re-) and segmented watermarking techniques is to be implemented with a multi-purpose evolutionary algorithm. Genetic algorithm is adopted to determine the embedding locations and scaling factors for different watermarks according to the features of each host image to balance between imperceptibility and robustness. The wavelet transform is utilized for salient features extraction because of its excellent space-frequency localization of salient image features. In addition, the suggested model encrypts the watermarks with the aid of Walsh transform; so that it is difficult to handle the watermarks even after being extracted by the attackers. Experimental results show that the proposed model is more robust against common image manipulation attacks in terms of PSNR and NCC.

A High Result in Wavelet Watermarking Using Singular Value Decomposition

Internet that has developed into a good distribution tool for digital data, causing a large increase in digital data sharing, especially in the form of digital images, and causing problems that need attention. One of them is about copyright protection. Watermarking is one technique that aims to protect digital image copyright. In this study, watermarking was carried out using the Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) algorithms in digital images with different file extensions. Transformation of 2 levels of DWT and SVD on the host image and SVD transformation on the watermarked image that inserted in the LL2 sub-band of the host image. Watermarking with the proposed method produces good image quality with PSNR values exceeding 40 dB, SSIM reaching 0.99 and NCC reaching 1. This shows a robust and imperceptible watermarking image.

APPLYING WATERMARKING IN DIGITAL IMAGE COPYRIGHT PROTECTION

Nowadays, with the rapid development of the Internet, the transmission of digital data such as images, videos and texts through the Internet becomes more convenient. Therefore, how to protect the integrity and copyright of digital data has become an urgent issue. This paper presents a watermarking method that based on Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT) and Singular Value Decomposition (SVD) in order to protect copyright of digital images. The experimental results show that the quality of watermarked images are maintained good with high robustness against various attacks and watermark can be extracted from embedded image without original image.

Hybrid and blind watermarking scheme in DCuT – RDWT domain

In this paper, a hybrid and blind watermarking scheme is proposed for the protection of copyright of digital images. The scheme based on hybridization of two advance transforms such that discrete curvelet transform (DCuT) and redundant discrete wavelet transform (RDWT). The motivation behind using these two transforms combination to improve the imperceptibility of the watermarking scheme. The imperceptibility requirement of the scheme is achieved using hybrid coefficients which are achieved by applying single level RDWT to the high frequency curvelet coefficients of the cover image. The watermark information is inserted by modifying the coefficients of the wavelet coefficients of LH subband using PN sequences according to watermark bit and gain factor. The security of the proposed scheme is achieved by applying Arnold scrambling to watermark image before embedding. Experiments of the proposed scheme are conducted on various types of natural images. Experiments results show that, compared with existing schemes, the proposed scheme is robust to various attacks while having high imperceptibility. Also, the proposed scheme is performed better than many existing schemes.

Deep neural network-based image copyright protection scheme

A deep neural network-based image copyright protection scheme is presented. Instead of modifying the images like traditional watermarking methods, the proposed scheme trains a neural network to extract the robust features from image blocks and then classify them to represent the copyright message. First, the original image and its multiple attacked images are divided into nonoverlapping blocks, a part of which will be selected as candidate blocks. Then, the copyright message bits, together with candidate blocks, constitute the training dataset for the network, enabling the trained network to serve as a copyright message extractor. With the proposed scheme, no quality loss will be caused, and moreover, superior robustness can be achieved due to the adaptive robust feature extraction. Our study also offers further insight into the rationalities and considerations in design. Extensive experiments on a wide range of images show that the proposed scheme possesses strong robustness to many attacks, including additive noise corruption, JPEG compression, filtering, and resizing.

Convolutional neural networks-based stereo image reversible data hiding method

For copyright and integrity protection of stereo images, a stereo image reversible data hiding (SIRDH) method based on the convolutional neural network (CNN) is presented. To increase the pixel prediction, a CNN-based predictor is designed. Firstly, pixels are divided into two types. For predicting one type of pixels in one view, the other type of pixels in the same view is considered as the low-resolution (LR) image. Secondly, a LR difference view between the LR image and the other view is computed, since the difference view consists of the texture and depth information. Then, CNN is trained to recover the high-precision difference view from the LR difference view, and the high-resolution image is computed to predict pixels accurately. Moreover, the prediction error expansion (PEE) is employed to embed data. Experimental results show that the proposed method is superior to existing SIRDH methods.

An improved watermarking algorithm for color image using Schur decomposition

In order to protect the color image copyright protection of the multimedia big data, it is necessary to design a color image watermarking algorithm. To achieve this purpose, an improved color image watermarking algorithm based on Schur decomposition is proposed in this paper. First, the watermark information is, respectively, embedded into the upper triangular matrix and the unitary matrix of Schur decomposition by two different methods, and two temporary watermarked image blocks are obtained. Then, the proposed improved method is used to select the final watermarked image block from these temporary watermarked image blocks. The highlight of the proposed method is that the final watermarked block has less visual distortion. Meanwhile, the embedded flag is created and uploaded to the cloud service provider with the watermarked image. When extracting watermark, the original host image or the watermark image is not needed. Experimental results show that the proposed watermarking algorithm has better performance; in particular, the watermark invisibility has been obviously improved than other methods considered in this paper.