Copyright Protection Of Images Research Articles

Fast fractional-order polar linear canonical transform: Theory and application

Zero-watermarking is a promising technology for image copyright protection due to its excellent imperceptibility and robustness. Compared with deep learning (DL)-based zero-watermarking schemes which are time-consuming and unable to respond in real-time, the moment-based zero-watermarking schemes do not have the aforementioned drawbacks and have drawn great attention with their strong description ability and geometric invariance. However, most existing moment-based zero-watermarking methods bear a number of drawbacks, in particular: (i) Direct computation of image moments is inefficient and inaccurate; (ii) They have difficulty obtaining the favorable trade-off between robustness and discriminability; (iii) Generating pseudo-random numbers based on traditional logistic map results in their lower security performance. To deal with those issues, this paper introduces a new image zero-watermarking method that relies on fast fractional-order polar linear canonical transform (FFrPLCT) features and asymmetric tent map. Firstly, we propose a novel computation strategy called fast polar linear Canonical transform (FPLCT), to save the calculation time of moments. Secondly, we define the fast fractional-order polar linear Canonical transform (FFrPLCT), which is characterized by the generic nature and time-frequency analysis capability. Thirdly, we present the FFrPLCT mixed low-order features by fully exploiting the time-frequency property of FFrPLCT, to improve both the robustness and discriminability of image representation. Finally, we develop a new image zero-watermarking method using FFrPLCT domain mixed low-order features and asymmetric tent map. Experimental results and comparison with well-known existing methods demonstrate the efficacy and superiority of the proposed image zero-watermarking scheme.

Adaptive multiple zero-watermarking based on local fast quaternion radial harmonic Fourier moments for color medical images

The copyright protection of medical images is receiving increasing attention. Zero-watermarking schemes are a critical technology for copyright protection of medical images and show better imperceptibility performance than embedded watermarking schemes. However, existing zero-watermarking schemes still have some limitations that prevent them from fully exploiting their potential, including failure against complex desynchronization attacks and high computational complexity. To this end, we propose a novel zero-watermarking scheme based on fast quaternion radial harmonic Fourier moments (FQRHFMs) that is resistant to desynchronization attacks. Specifically, this article formulates multiple local feature regions (LFRs) based on a speeded-up robust feature (SURF) operator and provides a fast computation method for QRHFMs by using fast Fourier transform (FFT). The magnitudes of FQRHFMs are computed in each incomplete overlapping LFR for generating multiple zero-watermarks to resist desynchronization attacks. Experimental results show that the proposed scheme achieves state-of-the-art robustness against various desynchronization attacks (e.g., translation, cropping, and length-width ratio changing), and outperforms existing local zero-watermarking frameworks with regard to accuracy and efficiency.

A Robust and Secure Watermarking Approach Based on Hermite Transform and SVD-DCT

Currently, algorithms to embed watermarks into digital images are increasing exponentially, for example in image copyright protection. However, when a watermarking algorithm is applied, the preservation of the image’s quality is of utmost importance, for example in medical images, where improper embedding of the watermark could change the patient’s diagnosis. On the other hand, in digital images distributed over the Internet, the owner of the images must also be protected. In this work, an imperceptible, robust, secure, and hybrid watermarking algorithm is presented for copyright protection. It is based on the Hermite Transform (HT) and the Discrete Cosine Transform (DCT) as a spatial–frequency representation of a grayscale image. Besides, it uses a block-based strategy and a perfectibility analysis of the best embedding regions inspired by the Human Vision System (HVS), giving the imperceptibility of the watermark, and a Singular-Value Decomposition (SVD) approach improved robustness against attacks. In addition, the proposed method can embed two watermarks, a digital binary image (LOGO) and information about the owner and the technical data of the original image in text format (MetaData). To secure both watermarks, the proposed method uses the Jigsaw Transform (JST) and the Elementary Cellular Automaton (ECA) to encrypt the image LOGO and a random sequence generator and the XOR operation to encrypt the image MetaData. On the other hand, the proposed method was tested using a public dataset of 49 grayscale images to assess the effectiveness of the watermark embedding and extraction procedures. Furthermore, the proposed watermarking algorithm was evaluated under several processing and geometric algorithms to demonstrate its robustness to the majority, intentional or unintentional, attacks, and a comparison was made with several state-of-the-art techniques. The proposed method obtained average values of PSNR = 40.2051 dB, NCC = 0.9987, SSIM = 0.9999, and MSSIM = 0.9994 for the watermarked image. In the case of the extraction of the LOGO, the proposal gave MSE = 0, PSNR ≫ 60 dB, NCC = 1, SSIM = 1, and MSSIM = 1, whereas, for the image MetaData extracted, it gave BER = 0% and Berror=0. Finally, the proposed encryption method presented a large key space (K=1.2689×1089) for the LOGO image.

Zero-watermark scheme for medical image protection based on style feature and ResNet

Zero-watermarking technology is of major interest within the field of medical image copyright protection because this embedding method does not cause loss of images. However, the features used to construct the zero-watermark in existing methods are destroyed after geometric attacks, particularly strong geometric attacks. This destruction causes the final extracted watermark image to lose its details and fail copyright protection. This study proposes a zero-watermark medical image protection scheme based on style features and a residual network to solve this concern. The style features extracted based on deep neural networks are high-order statistics of image details and abstract features and have good robustness against geometric attacks, such as rotation and scale. Simultaneously, this study proposes a zero-watermark verification method based on the residual network to replace the traditional XOR11The full name is exclusive OR, abbreviated as xor, which is a common logical operation in the computer field. operation. The residual network can iteratively learn to extract the watermark image from the zero-watermark image and enhance the quality of the watermark image using the designed loss function. We experimentally demonstrated that the residual network outperformed in reconstructing watermark images. This scheme can resist common geometric and strong image attacks, performance is superior to that of similar zero-watermarking schemes.

Research on the Improvement of LSB-based Image Steganography Algorithm

This study has made an improvement based on the LSB algorithm, which uses a randomly generated sequence for embedding information, with an implementation environment of Python and a combination of OpenCV By analyzing the embedded data with PSNR values and pretzel-plus-noise attacks, the results show that this method has better image quality and stronger resistance to attacks, while the complexity of extracting the embedded information by external users is high. The improved LSB algorithm in this study has great reference value for information covert transmission, and can be used for image copyright protection and privacy information protection in practical applications.

A Powerful Zero-Watermarking Algorithm for Copyright Protection of Color Images Based on Quaternion Radial Fractional Hahn Moments and Artificial Bee Colony Algorithm

A Powerful Zero-Watermarking Algorithm for Copyright Protection of Color Images Based on Quaternion Radial Fractional Hahn Moments and Artificial Bee Colony Algorithm

Copyright protection of medical images: A view of the state-of-the-art research and current developments

Copyright protection of medical images: A view of the state-of-the-art research and current developments

Fast Frequency Domain Screen-Shooting Watermarking Algorithm Based on ORB Feature Points

With high performances of image capturing tools, image information can be easily obtained by screenshots that make image copyright protection a challenging task. The existing screen-shooting watermarking algorithms suffer from a huge running time, in addition to their low robustness against different screenshot attacks, such as different distances and capturing angles of the screenshots. In this paper, a fast and robust high-capacity flexible watermarking algorithm for screenshot images is proposed. Firstly, Oriented FAST and Rotated BRIEF (ORB) feature points are extracted from the input image. Secondly, the feature points are then sorted in a descending order according to their response values. Then, the first five non-overlapping feature points are selected for the embedding by using Hamming window-based filtering method. Furthermore, we exploit the multi-resolution property of Discrete Wavelet Transform (DWT) and energy compaction property of Singular Value Decomposition (SVD) to embed the watermark. Therefore, the classical DWT combined with Singular Value Decomposition (SVD) are adopted to improve the robustness and capacity of the proposed watermarking algorithm. At the extraction side, the sum of the response values for the three RGB channels of the color-ripped image is calculated to improve the feature point localization accuracy. Experimental results show that the proposed screen-shooting watermarking algorithm improves running speed while ensuring the robustness. Furthermore, it has less time complexity and high robustness compared with the state-of-the-art watermarking algorithms against different screenshot attacks.

Security Analysis and Improvement of Dual Watermarking Framework for Multimedia Privacy Protection and Content Authentication

The demand for using multimedia network infrastructure for transmission grows with each passing day. Research scholars continue to develop new algorithms to strengthen the existing network security framework in order to ensure the privacy protection and content authentication of multimedia content and avoid causing huge economic losses. A new technology for multimedia image copyright protection and content authentication has been proposed. The innovations lie in the use of an inter-block coefficient difference algorithm to embed robust watermarking in the transform domain, and the same fragile watermark is embedded twice in the spatial domain so that any tiny tampering can be identified and located. A new encryption algorithm combined with Arnold transform is used to encrypt data before embedding. However, some security vulnerabilities were found, and successful cryptanalysis and attack were conducted. Subsequently, an improved scheme was proposed to improve the security and tamper detection ability of the original watermarking scheme and recover the tampered robust watermark. The results show that the improved scheme is safer and more reliable and shows good performance in tampering detection and the recovery robustness of the watermark.

Robust Watermarking Techniques for the Authentication and Copyright Protection of Digital Images: A Survey

Digital image authentication and security are crucial concerns for the digital revolution since any image may be readily tampered with. Digital watermarking schemes were since been utilized to tackle a range of problems over time and involving the verification of digital images and copyright protection. In a real-world setting, watermarked contents are frequently subject to a succession of assaults which makes it necessary to strike a balance between resilience and imperceptibility in the face of attacks. There are numerous hazards to this, and numerous watermarking techniques have been created to counter them. Data with less perceptual distortion should be able to be included in a real watermarking technique in addition to restoring the original cover content. As a result, robustness, imperceptibility, and security are three crucial criteria for digital content'sauthentication and copyrightpreservation. This study therefore presents a careful review of some cutting-edge watermarking technologies used for copyright protection and authentication so as to identify their strengths and limitations. For clarity, this study shall explain some basic concepts of digital watermarking as well as the various forms of attacks on watermarks. The contributions from this work will be useful to researchers aim at developing efficient watermarking techniques

Blockchain‐based reliable image copyright protection

AbstractThe indiscriminate distribution of a large number of unlicensed images through the Internet seriously harms the benefits of image owners, which prompts the study of image copyright protection solutions. Existing blockchain‐free solutions are limited to using centralized servers to store copyright information, leaving data vulnerable to being lost or tampered with by external attacks. Although the blockchain‐based image copyright protection solutions are capable of addressing the above problem, improvements are needed in choosing a suitable blockchain platform and supporting integrated copyright life cycle management. To this end, this paper designs a blockchain‐based reliable image copyright protection system named BB‐RICP using Hyperledger Fabric. For one thing, the adoption of Fabric mitigates the limitations of other blockchain platforms represented by Ethereum in terms of efficiency, economy, and availability. For another, BB‐RICP successes in achieving integrated copyright lifecycle management. In addition, BB‐RICP achieves enhanced applicability performance by firstly introducing GM algorithms recommended by Chinese national standard and adapting the more consortium blockchain‐oriented practical byzantine fault tolerance algorithm. Moreover, the adoption of spread spectrum watermarking brings convenience to users. Finally, Kubernetes is used to assist in the simulation of BB‐RICP to verify that users can operate reliably in the blockchain network.

Multi-dimensional hypercomplex continuous orthogonal moments for light-field images

Image moments have always been topical in the domain of image processing, and the proposed hypercomplex moments and multi-channel moments have greatly broadened the application of image moments in recent years. However, the hypercomplex moments are limited by the specific number of imaginary parts of the hypercomplex number, and the redundancy of imaginary parts or the overflow of image channels will occur when the number of imaginary parts does not fit the image structure. The multi-channel moments allow flexible adjustment of the number of channels, but their loose structure will result in the loss of correlation between multiple channels of images. Moreover, the hypercomplex moments and multi-channel moments cannot handle images with multi-dimensional structures such as light-field (LF) images. For the purpose of addressing the above problems, this paper proposes generalized hypercomplex continuous orthogonal moments (HCOMs) and extends them to multi-dimensional hypercomplex continuous orthogonal moments (MHCOMs) in multi-dimensional space. MHCOMs can be used to process images with arbitrary multi-dimensional structures, and when they are used for LF image processing, there is no need to map the LF images to two-dimensional space to change the multi-dimensional structural properties of LF images. By calculating MHCOMs of LF images, a set of multi-dimensional hypercomplex tensors containing robust feature information of LF images can be obtained, and the original LF images can be reconstructed using this information. Furthermore, the MHCOMs-based zero-watermarking scheme is designed for LF images, which has excellent robustness and can achieve lossless copyright protection for LF images.

CADW: CGAN-Based Attack on Deep Robust Image Watermarking

Robust watermarking plays an essential role in copyright protection for digital images. Meanwhile, the studies of robust image watermarking and corresponding attack methods promote and complement each other. Because the traditional attack methods are weak to attack the deep watermarking, in this work, we thus design an effective watermarking attack method based on the conditional generative adversarial nets (CGAN). Also, according to the network structure of CGAN, a targeted and combined loss function is constructed, which can guarantee acceptable visual quality of attacked image and make the watermark extraction fail simultaneously. Experimental results demonstrate that our method is effective for some state-of-the-art deep robust image watermarking methods with the transferability. In addition, as an attack method, it can be regarded as an evaluation standard to measure the robustness of watermarking.

Cross-scale feature fusion-based JND estimation for robust image watermarking in quaternion DWT domain

Owing to the rapid development of just-noticeable difference (JND) and the high robustness of discrete wavelet transform (DWT) based watermarking, robust watermarking methods based on JND models have been extensively adopted in the area of image copyright protection. In general, in existing JND model-based methods, transform domain-based features play an important role during the quantization strength measurement. However, most existing methods only use the subband-specific features from the final multi-scale wavelet transform domain, ignoring the feature relevance among subband-specific features with different scales among RGB channels. To address this issue, in this study, we put forward a JND estimation based on cross-scale feature fusion (CFJnd) mechanism in quaternionic DWT domain for robust image watermarking. For the proposed CFJnd, we first design different quaternionic wavelet scales for the JND modeling, which can be used to measure the minimum distortion level of the embedding-specific subband relevance. Furthermore, the cross-scale features among different subbands are adopted to jointly generate the pattern, texture and color measurement, making the final perceptual masking more representative. In addition, we further develop a CFJnd-based robust image watermarking, and the watermark is embedded by quantifying the candidate quaternionic DWT coefficients of the embedding-specific subband on a level which is adaptively defined according to the proposed CFJnd. Experimental results based on the publicly available image database show that the proposed method can produce reliable and promising results, compared to other state-of-the-art image watermarking methods.

Robust and secured watermarking using Ja-Fi optimization for digital image transmission in social media

Widespread transmission of digital image in social media has come up with security, confidentiality and authentication issues. Ensuring copyright protection of digital images shared through social media has become inevitable. To address these issues, a robust and secure digital image watermarking scheme using Redundant discrete wavelet transform (RDWT) - Singular value decomposition (SVD) hybrid transform is proposed in this paper. In the proposed scheme, digital image is divided into 4 × 4 non-overlapping blocks, and low information blocks are selected for embedding to ensure higher imperceptibility. For watermark embedding 1-level RDWT is applied on the selected blocks followed by SVD decomposition to make the proposed scheme highly robust against common attacks. One watermark bit is embedded in each left and right singular SVD matrices by adjusting the coefficients. This makes the proposed scheme free from false positive error and achieve high embedding capacity. Before embedding, watermark encryption is done by using a pseudo random key. The pseudo random key is generated adaptively from the cover image by using discrete wavelet transform saliency map, block mean approach and cosine functions. High imperceptibility and robustness is indispensable for the digital images shared through social media. But, these watermarking characteristics are in trade-off. In the proposed scheme, the trade-off is balanced by using optimized scaling factor (embedding strength). Scaling factor is optimized by using the proposed JAYA-Firefly (Ja-Fi) optimization. Experimental results demonstrate that the proposed scheme provides high imperceptibility, robustness, embedding capacity and security. Furthermore, performance comparison with the recent state-of-the-art schemes affirms that the proposed scheme has superior performance.

Digital Watermarking-Based Cryptosystem for Cloud Resource Provisioning

Cloud computing resource privacy is important and it becomes stronger when image-based security is applied. Most cloud service providers provision resources for images to the end users. Numerous encryption strategies are applied to safeguard information of the image while empowering visual component extractions. The work uses wavelet domain technique, visual cryptography, and Arnold transformation. This scheme provides additional security features to the secret share image at the trusted authority side for copyright protection of digital images. The proposed technique is robust against some selected attacks like scaling, blurring, etc. This technique protects the copyright of digital data over the cloud. It is a need and necessary to protect and prevent the illegal copying, redistribution, and copyright infringement of multimedia. This research work aims at increasing robustness and security of the digital image copyright scheme. The proposed scheme is a hybrid authentication framework that will perform better in the watermarking system of security using simulation over MATLAB.

A Hyper-Chaotically Encrypted Robust Digital Image Watermarking Method with Large Capacity Using Compress Sensing on a Hybrid Domain.

The digital watermarking technique is a quite promising technique for both image copyright protection and secure transmission. However, many existing techniques are not as one might have expected for robustness and capacity simultaneously. In this paper, we propose a robust semi-blind image watermarking scheme with a high capacity. Firstly, we perform a discrete wavelet transformation (DWT) transformation on the carrier image. Then, the watermark images are compressed via a compressive sampling technique for saving storage space. Thirdly, a Combination of One and Two-Dimensional Chaotic Map based on the Tent and Logistic map (TL-COTDCM) is used to scramble the compressed watermark image with high security and dramatically reduce the false positive problem (FPP). Finally, a singular value decomposition (SVD) component is used to embed into the decomposed carrier image to finish the embedding process. With this scheme, eight grayscale watermark images are perfectly embedded into a carrier image, the capacity of which is eight times over that of the existing watermark techniques on average. The scheme has been tested through several common attacks on high strength, and the experiment results show the superiority of our method via the two most used evaluation indicators, normalized correlation coefficient (NCC) values and the peak signal-to-noise ratio (PSNR). Our method outperforms the state-of-the-art in the aspects of robustness, security, and capacity of digital watermarking, which exhibits great potential in multimedia application in the immediate future.

A multiple transform based approach for robust and blind image copyright protection

SummaryDigital image sharing and utilization have increasing in a speedy manner at present time. Therefore, copyright/ownership protection for digital images has been an essential requirement in the modern world of digital advancements. This work offers an image watermarking scheme to provide ownership/copyright verification in an effective manner with no conciliation with imperceptibility. The image is first partitioned into small size blocks. During embedding, a multilevel transform domain‐based framework is employed to embed the watermark information into blocks. Additionally, the block selection process is made randomize (key‐based) to offer high security against illegal manipulations/access. Before embedding, the watermark is encrypted using the Arnold transform‐based approach for additional security. The scheme has blind nature, high imperceptibility and it is robust enough to endure a different variety of processing attacks. Experimental results on different images illustrate that the proposed watermarking approach has high imperceptibility, high robustness, decent embedding capacity, and significant security features. The relative comparison with the existing robust watermarking schemes (having the same payload) shows the superiority of the proposed work over existing methods presented in the recent past.

A highly robust and secure digital image watermarking using modified optimal foraging algorithm - based SVM classifier and hyperchaotic Fibonacci Q-matrix

Transmission media is at rise over the internet, due to which the copyright risk is alarming. In such situation, enhanced security is the main concern. Digital image watermarking is the technique that ensures the copyright protection, security, and authenticity of the digital image. This research work recommends a highly secured and robust digital image watermarking system. In this method, the cover image is confused by arbitrarily generated numbers by a six-dimensional hyperchaotic technique, then this permuted image is scattered by applying the Fibonacci Q matrix to generate a scattered host image. This scattered image is decomposed up to 3 levels through DWT and the low pass sub-band caused by DWT are further decomposed by SVD. Singular values generated by SVD are used for watermark embedding as a slight change in the value does not affect the image quality. SVM classifier is used to classify the appropriate location to insert the scattered binary watermark. In this method SVM parameters are optimized by a modified optimal foraging algorithm, so that classification error can be reduced. Pixel rearrangement of the watermark image and host image makes the proposed method more secure, and it is highly robust as SVM is trained to classify locations that are less distorted by noise. Experimental outcomes depicts that the proposed method is accurate and better to the current cutting-edge methods in terms of security and robustness of digital image watermarking, as PSNR is approx. 72db and NC values are 1 after applying all the possible attacks.

Digital Watermarking System for Copyright Protection and Authentication of Images Using Cryptographic Techniques

Digital images are transferred with ease through the network. Many users are using the images without the knowledge of the owners. Therefore, a novel watermarking scheme is proposed to ensure copyright protection and authentication of images using cryptography techniques. Here, a quick response (QR) image is generated for a watermark image that contains public and private keys prepared using a cryptosystem. Later, this QR image is scrambled using a chaotic logistic map. The public and private keys are used to cipher and decipher the data. Next, the scrambled QR watermark is embedded into a color image using a single-level discrete wavelet transform followed by singular value decomposition using the key value. Finally, the inverse process is applied to extract the watermark. The proposed method is validated using various image processing attacks. The results are then compared with state-of-the-art watermarking schemes. The experimental results show that the scheme provides good results in terms of robustness and imperceptibility.