Digital Watermarking Applications Research Articles

Extreme multi-stability and microchaos of fractional-order memristive Rulkov neuron model considering magnetic induction and its digital watermarking application

Extreme multi-stability and microchaos of fractional-order memristive Rulkov neuron model considering magnetic induction and its digital watermarking application

Hadamard Error-Correcting Codes and Their Application in Digital Watermarking.

In communication technologies such as digital watermarking, wireless sensor networks (WSNs), and visual light communication (VLC), error-correcting codes are crucial. The Enhanced Hadamard Error-Correcting Code (EHC), which is based on 2D Hadamard Basis Images, is a novel error correction technique that is presented in this study. This technique is used to evaluate the effectiveness of the video watermarking scheme. Even with highly sophisticated embedding techniques, watermarks usually fail to resist such comprehensive attacks because of the extraordinarily high compression rate of approximately 1:200 that is frequently employed in video dissemination. It can only be used in conjunction with a sufficient error-correcting coding method. This study compares the efficacy of the well-known Reed-Solomon Code with this novel technique, the Enhanced Hadamard Error-Correcting Code (EHC), in maintaining watermarks in embedded videos. The main idea behind this newly created multidimensional Enhanced Hadamard Error-Correcting Code is to use a 1D Hadamard decoding approach on the 2D base pictures after they have been transformed into a collection of one-dimensional rows. Following that, the image is rebuilt, allowing for a more effective 2D decoding procedure. Using this technique, it is possible to exceed the theoretical error-correcting capacity threshold of ⌊dmin-12⌋ bits, where dmin is the Hamming distance. It may be possible to achieve better results by converting the 2D EHC into a 3D format. The new Enhanced Hadamard Code is used in a video watermarking coding scheme to show its viability and efficacy. The original video is broken down using a multi-level interframe wavelet transform during the video watermarking embedding process. Low-pass filtering is applied to the video stream in order to extract a certain frequency range. The watermark is subsequently incorporated using this filtered section. Either the Reed-Solomon Correcting Code or the Enhanced Hadamard Code is used to protect the watermarks. The experimental results show that EHC far outperforms the RS Code and is very resilient against severe MPEG compression.

Fractional-order heterogeneous memristive Rulkov neuronal network and its medical image watermarking application

This article proposes a novel fractional heterogeneous neural network by coupling a Rulkov neuron with a Hopfield neural network (FRHNN), utilizing memristors for emulating neural synapses. The study firstly demonstrates the coexistence of multiple firing patterns through phase diagrams, Lyapunov exponents (LEs), and bifurcation diagrams. Secondly, the parameter related firing behaviors are described through two-parameter bifurcation diagrams. Subsequently, local attraction basins reveal multi-stability phenomena related to initial values. Moreover, the proposed model is implemented on a microcomputer-based ARM platform, and the experimental results correspond to the numerical simulations. Finally, the article explores the application of digital watermarking for medical images, illustrating its features of excellent imperceptibility, extensive key space, and robustness against attacks including noise and cropping.

A non-invasive method for the cataloguing and authentication of surveillance video using on-camera blockchain participation, machine learning and signal analysis

Presented here is a non-invasive system capable of cataloguing, identifying, and authenticating surveillance video throughout its lifecycle, with particular application to law enforcement. It delivers benefits similar to digital watermarking by utilising signal processing, machine learning object detection and a supporting blockchain infrastructure, and is proposed as a method for managing large volumes of data whilst overcoming issues associated with real time application of digital watermarking or hashing. A functional reference system is tested for effectiveness and its performance is analysed on test data, including evaluation of four search optimisation strategies, with a clear performance ranking shown. The system allows for the ability to identify and evaluate video integrity without requiring modification or access to the original video, making it of specific interest to law enforcement applications.

Watermarking System for Medical Images Using Optimization Algorithm

One of the main methods used to provide security for medical records when exchanging these records through open networks is digital watermarking. In order to preserve the privacy of patients, this system also requires a means to secure images. In this paper, a watermarking based on discrete wavelet transform (DWT), and discrete and discrete cosine transform (DCT) in cascade provides more robustness and security. DCT divides the image into low and high-frequency regions, watermarking message can be embedded into low-frequency regions to prevent distortion of the original image. DWT splits the image into four frequency coefficients; horizontal, vertical, approximation, and detailed frequency component. The judgment factors for the strength of the watermark system are robustness, invisibility, and embedded message capacity. Invisibility means transparency of the watermark logo or data in the original or host image without any distortion. Capacity data payload means the size of the embedded image which is related to the amount of data or logo size that will be embedded in the host image. Robustness refers to the capability of the watermark to stand with the host image operations. In this paper, we propose an optimizer to trade-off between robustness, invisibility, and message capacity. Three metrics were employed to assess the results achieved by the proposed approach, namely, Peak Signal-to-Noise Ratio (PSNR), Normalized Cross Correlation (NCC), and Image Fidelity (IF). The achieved results confirmed the effectiveness and superiority of the proposed approach for real-world digital watermarking applications.

Dynamic analysis and application in medical digital image watermarking of a new multi-scroll neural network with quartic nonlinear memristor.

Memristor is widely used in various neural bionic models because of its excellent characteristics in biological neural activity simulation. In this paper, a piecewise nonlinear function is used to transform the quartic memristor, which is introduced into the ternary Hopfield neural network (HNN) with self-feedback, and a piecewise quartic memristive chaotic neural network model with multi-scroll is constructed. Through simulation analysis, the number of scroll layers changes with memristor parameters and has significant coexistence of multi-scroll attractors and high initial value sensitivity has been found. Using its excellent unpredictability, a digital watermarking algorithm based on wavelet transform is improved and used in the protection of personal medical data. The results show that it not only improves the confidentiality and convenience, but also ensures its robustness and has good encryption effect.

Watermarking schemes for digital images: Robustness overview

Digital watermarking is an important scientific direction located at the intersection of cybersecurity and multimedia processing. Digital watermarking is used for digital objects copyright protection and protection against forgery. The importance of those tasks is highlighted by the ongoing COVID-19 pandemic that lasts for more than a year and forced multiple industries to transit to online. The main digital watermarking application include active attackers whose goal is to destroy or damage watermarks. Thus, digital watermarking schemes must be robust to attacks. Despite of the large number of existing digital watermarking schemes, a comprehensive analysis of their robustness towards various attacks does not exist. Our study aims to fill this gap. In this article, latest years findings in digital watermarking are systematized. First of all, we review the most prominent distinctive features of watermarking schemes, attack types, and performance measures to facilitate navigation in digital image watermarking. Then, we introduce classification of digital watermarking schemes by their robustness towards various classes of attacks. We believe this classification could be useful for researchers who aim to choose a digital watermarking scheme for their application with a known set of attacks. Finally, we highlight the most promising solutions that further development could lead to schemes with better robustness compared to existing schemes.

A Digital Watermarking Encryption Technique Based on FPGA Cloud Accelerator

Digital watermarking has the properties such as invisibility and anti-aggression, so the digital watermarking technology has been widely used in copyright protection, information hiding. The watermarking technology takes into account the invisibility and robustness of the watermark by controlling the embedding intensity and position of the watermark mainly in the transformation domain. In this paper, discrete cosine transform (DCT) is adopted to transform the given image from spatial domain to frequency domain for adding watermark information. In order to meet the demands of image watermarking batch processing and cloud processing in the future, this paper optimized the DCT algorithm and the data precision, and successfully deployed the designed accelerator kernel on the FPGA cloud platform to speed up the processing of watermarking. The implementation of data processing based on cloud platform is the development trend of big data era. The cloud platform adopted in this paper is based on the OpenCL heterogeneous architecture combining CPU and FPGA. The cloud-based implementation makes digital watermarking application highly extensible, widely shareable, and more secure. The whole system implements a series of complete cloud processes including image decoding, image preprocessing, watermark embedding, and watermarked image encoding. The watermarking algorithm is accelerated by the efficient parallel computing capabilities of FPGA. It can be seen that the result of acceleration is remarkable, providing the state-of-the-art throughput of 1.676 GBps and the highest processing speed of 937 FPS for $800\times800$ sized colorimage.

Fusing PDTDFB magnitude and relative phase modeling for geometrical correction-based image watermarking

Robustness, which refers to the ability that watermark signal survives various attacks, like additive noise, compression, rotation, etc., has played extremely important role in the multiple applications of digital watermarking. As one of the most difficult kinds of signal processing operations for a digital watermark to survive, geometric distortions have become a central problem in image watermarking research. Therefore, developing a greatly robust digital image watermarking approach, which can withstand geometrical distortions, remains a quite challenging work. In this paper, a new geometrical correction-based image watermarking approach using PDTDFB magnitude and relative phase modeling is proposed. This approach consists of digital watermark embedding, geometric distortions correction, and digital watermark extraction. In the watermark embedding process, PDTDFB (Pyramidal dual-tree directional filter bank) decomposition is performed on the original host image, followed by the low-pass subband partitioning. Watermark bit is inserted into low-pass subband block by modifying (quantization index modulation, QIM) the set of low-pass PDTDFB coefficients. In the geometric correction, the PDTDFB magnitude and relative phase are modeled by using Weibull distribution and Vonn distribution, respectively. Utilizing the compact statistical model parameters, the LS-SVR (Least squares support vector regression) correction is performed to estimate the geometrical distortions parameters. After LS-SVR geometrical correction, the watermark bits are extracted from the watermarked low-pass subband by employing the inverse QIM. Experimental results confirm that, under various well-known practical attacks, including common signal processing operations and geometrical distortions, the proposed approach performs well compared to conventional image watermarking methods.

Large Families of “Grey” Arrays with Perfect Auto-correlation and Optimal Cross-Correlation

Digital watermarking applications have a voracious demand for large sets of distinct 2D arrays of variable size that possess both strong auto-correlation and weak cross-correlation. We use the discrete Finite Radon Transform to construct “perfect” \(p \times p\) arrays, for p any prime. Here the array elements are comprised of the integers \(\{0,\pm 1,+2\}\). Each array exhibits perfect periodic auto-correlation, having peak correlation value \(p^2\), with all off-peak values being exactly zero. Each array, by design, contains just \(3(p-1)/2\) zero elements, the minimum number possible when using this “grey” alphabet. The grey alphabet and the low number of zero elements maximises the efficiency with which these perfect arrays can be embedded into discrete data. The most useful aspect of this work is that large families of such arrays can be constructed. Here the family size, M, is given by \(M = p^2-1\). Each of the \(M(M-1)/2\) intra-family periodic cross-correlations is guaranteed to have one of the three lowest possible merit factors for arrays with this alphabet. The merit factors here are given by \(v^2/(p^2-v^2)\), for \(v = 2\), 3 and 4. Whilst the strength of the auto-correlation rises with array size p as \(p^2\), the strength of the many (order \(p^4\)) cross-correlations between all M family members falls as \(1/p^2\).

A multiple watermarking algorithm for vector geographic data based on coordinate mapping and domain subdivision

A lot of watermarking algorithms for vector geographic data are presented in the literature. Due to widely application of digital watermarking, more demands are required, such as multiple watermarking algorithm. However, vector geographic data attracted less research focus on multiple watermarking. Consequently, a multiple watermarking algorithm for vector geographic data is proposed. In particular, the vertices are mapped to the logic domains firstly based on the constructed function. Then every domain is subdivided into blocks according to dichotomy and the number of embedding watermarks. Then, every watermark is embedded in the corresponding block. During the watermark detection, the watermarks are detected without the original vector geographic data. Finally, the experiments are made to test the multiple watermark capacity and robustness against attacks, with an emphasis on cropping attacks. The experimental results show that the proposed algorithm has good robustness against common attacks, such as, data simplification, vertex addition, vertex deletion, feature deletion, and cropping attacks. Moreover, the algorithm provides high multiple watermark capacity.

PENERAPAN DIGITAL WATERMARK SEBAGAI VALIDASI KEABSAHAN GAMBAR DIGITAL DENGAN SKEMA BLIND WATERMARK

Digital watermarking is an important field of technological development that has now grown in the digital era. Digital era encourage the spread digital images on internet by the websites with a large scale. On the other hand, digital images are objects that are very easy to change or manipulate, and even copied irresponsibly. Meanwhile it is very difficult to prove the image has been changed by existing equipment at this time, and it is difficult to prove its ownership. This is an important issue, when the image is one of the evidences for legal cases, news reporting and medical filing, where the image must be ensured that the digital image is not subject to change or manipulation. In this paper, we present the application of digital watermarking to authentication and ownership validation of digital image so the image can be ascertained its validity. This research applies blind watermark scheme by using secret key that inserted at least-significant bits (LSB) of host image therefore the watermark is invisible watermark. The result of watermarked image has a small decrease in quality with the mean value of PSNR and MSE about 34.08 and 14.62.

A Detailed Survey of Digital Watermarking Applications and Its Techniques

This paper describes the significance of digital water marking process. Watermarking is a process of hiding information in multimedia content like images and videos. Now a day it is major research area. Digital watermarking is one of the best solutions to protect content in web, content authentication and managing copyright information. Watermarking has been proposed for a long while to embed the secret information with images to stop reduces unauthorized access of the content. Watermarking and image compression is quiet different area. Rest of this paper we are going to elaborate what are all techniques that are exist so far in watermarking technology and subsequent sections classifies from the different perspectives. Watermarking is not only protecting the content, it increases the value of the content. There are numerous algorithms and procedures available for watermarking of images and videos etc., although this paper limits watermarking with images only.

Design of LDPC Decoder Based On FPGA in Digital Image Watermarking Technology

LDPC code and digital image watermarking technology, which is an effective method of digital copyright protection and information security, has been widely used. But this is a multi-disciplinary, multi technology application scheme. In order to realize FPGA design of LDPC decoder in the application scheme, an effective implementation method of digital watermarking application system must be found. In this paper, MATLAB software and Qt development environment are combined to achieve the digital watermarking application software design. It could get real-time input data for the LDPC decoder. Then the hardware of the LDPC decoder is primarily implemented by FPGA in the digital image watermarking system. And the serial port is used to make the output data of the decoder back to computer for verification. Through the simulation results, the Modelsim time simulation diagram is given, and the watermark image compared with the original image is got. The results show that the resource usage of our system is few, and the decoding rate is fast. It has a certain practical value.

Ambiguity attacks on robust blind image watermarking scheme based on redundant discrete wavelet transform and singular value decomposition

Among emergent applications of digital watermarking are copyright protection and proof of ownership. Recently, Makbol and Khoo (2013) have proposed for these applications a new robust blind image watermarking scheme based on the redundant discrete wavelet transform (RDWT) and the singular value decomposition (SVD). In this paper, we present two ambiguity attacks on this algorithm that have shown that this algorithm fails when used to provide robustness applications like owner identification, proof of ownership, and transaction tracking.

Performance Analysis of Image Watermarking Using Contourlet Transform and Extraction Using Independent Component Analysis

In this paper, performance analysis of digital image watermarking using contourlet transform is proposed. The ease of digital media modification and dissemination necessitates content protection beyond encryption.So information's are hidden as digital watermarks in multimedia enables protection mechanism in decrypted contents. Among emergent applications of digital watermarking, owner identification, proof of ownership and transaction tracking are applications that protect data by embedding the owner's information in it.The main challenge in exploring geometry in images comes from the discrete nature of the data. Thus, unlike other approaches, our approach starts with a discrete-domain construction and then studies its convergence to an expansion in the continuous domain. Many literature have reported about Discrete Wavelet Transform watermarking techniques for data security. However, DWT based watermarking schemes are found to be less robust against image processing attacks and the shift variance of Wavelet Packet Transform causes inaccurate extraction. In Contourlet transformation, original image is decomposed to two level using contourlet and the watermark is embedded in the resultant sub-bands. Sub-band selection is based on the value of Peak Signal to Noise Ratio (PSNR) that is calculated between watermarked and original image.In DWT-SVD watermarking technique, firstly original image is decomposed according to DWT and then watermark is embedded in singular values obtained by applying SVD.To extract the watermark, ICA-ML is used, it has a novel characteristic is that it does not require the transformation process to extract the watermark. Simulation results show that contourlet based watermarking scheme is robust against attacks such as Salt and Pepper noise, Median filtering and rotation. The performance measures like PSNR and Similarity measure are evaluated and compared with SVD algorithm to prove the robustness of the scheme. Simulations are carried out using Matlab Software.

Security in Telemedicine using DWT-CDCS

protection of digital media is the very first application that comes to mind for digital watermarking. In the past, duplicating artwork was quite complicated and requires great efforts to create the work looks just like the original. However, in present digital world it is very simple for anyone to duplicate or manipulate digital data. The digital image watermarking allows the watermark to be embedded visibly or invisibly in the original image for identification of the owner. This concept can also be used for other media, such as digital video and audio. Telemedicine is a well-known application of digital watermarking. In this application security & authentication for medical data is very important. Hiding the data into the medical image provide the security over the public network. Authentication verifies whether the image certainly belongs to the right patient Authentication of medical data used for further diagnosis and reference. This paper focused on the methods of medical image data hiding for security and authentication. High capacity data hiding is achieved with CDCS (Class Dependent Coding Scheme). As well as data is effectively hided with discrete wavelet transform. Embedding watermarks in RONI (region of non interest) protects the ROI (region of interest) of medical image, which is diagnostically important part of medical images. Segmentation plays an important role in medical image processing for separating the ROI from medical image.

Design and Implementation of FPGA-Based JPEG Decoding IP Core and its Application in Digital Watermarking

In this paper the digital watermarking algorithm deep into the field of integrated circuits combined with the JPEG image watermarking processes and SOPC technology, Verilog HDL language is used to design and implement of a reusable JPEG decoder IP core which can be embedded, realizing the JPEG decoding on FPGA platform and further completing the watermark embedding. The JPEG decoder is tested through the Modalism simulation software and would be revised until the simulation results become correct. Finally, the Altera development board EP2C70F896C6N of CycloneII series is used to complete the system design. The results prove that the system can run well, the program which can obtain a larger increase speed in exchange for consuming a little hardware resource does work.

Image Copyright Protection Watermark Algorithm Based on Spread Spectrum Technology

With the application of digital watermarking based on spread spectrum communication technology and the difficult control characteristics of watermark load intensity and invisibility, this paper considers the best compromise between watermark robustness and invisibility factors, and puts forward a digital watermarking algorithm using spread spectrum communication technology. By ultimate strength loading watermark test, the algorithm is verified to have good robustness. Chinese library classification number: TP391 literature identifier: A

False Negative probabilities in Tardos codes

Forensic watermarking is the application of digital watermarks for the purpose of tracing unauthorized redistribution of content. One of the most powerful types of attack on watermarks is the collusion attack, in which multiple users compare their differently watermarked versions of the same content. Collusion-resistant codes have been developed against these attacks. One of the most famous such codes is the Tardos code. It has the asymptotically optimal property that it can resist \(c\) attackers with a code of length proportional to \(c^2\). Determining error rates for the Tardos code and its various extensions and generalizations turns out to be a nontrivial problem. In recent work we developed an approach called the convolution and series expansion (CSE) method to accurately compute false positive accusation probabilities. In this paper we extend the CSE method in order to make it possible to compute a bound on the False Negative accusation probabilities.