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.

Robust Deep Image Watermarking:A Survey

In the era of internet proliferation,safeguarding digital media copyright and integrity,especially for images,is imperative.Digital watermarking stands out as a pivotal solution for image security.With the advent of deep learning,watermarking has seen significant advancements.Our review focuses on the innovative deep watermarking approaches that employ neural networks to identify robust embedding spaces,resilient to various attacks.These methods,characterized by a streamlined encoder-decoder architecture,have shown enhanced performance through the incorporation of novel training modules.This article offers an in-depth analysis of deep watermarking’s core technologies,current status,and prospective trajectories,evaluating recent scholarly contributions across diverse frameworks.It concludes with an overview of the technical hurdles and prospects,providing essential insights for ongoing and future research endeavors in digital image watermarking.

Boosting image watermarking authenticity spreading secrecy from counting-based secret-sharing

This study presents enhancing images authentication by securing watermarking hidden data via shares generated from counting-based secret sharing.The trustfulness of shares utilised secret-sharing as an applicable privacy creation tool for the authentication of real-life complex platforms.This research adjusts embedding the watermarking data over the images by innovative redistribution of shares to be embedded spread over all the images.The anticipated watermarking technique guaranteed to scatter the share bits implanting at different least significant bits of image pixels as boosting up the trust overall authentication practicality.The paper experimentation performance analysis shows that this improved image watermarking authentication(capacity)is averagely better by 33%–67%than other related exclusive-OR oriented and octagon approaches.Interestingly,these measurement improvements did not degrade the robustness and security of the system,inspiring our research for opening novel track of related future counting-based secret-sharing authentication progresses to come.

Robust Image Watermarking Using LWT and Stochastic Gradient Firefly Algorithm

Watermarking of digital images is required in diversified applicationsranging from medical imaging to commercial images used over the web.Usually, the copyright information is embossed over the image in the form ofa logo at the corner or diagonal text in the background. However, this formof visible watermarking is not suitable for a large class of applications. In allsuch cases, a hidden watermark is embedded inside the original image as proofof ownership. A large number of techniques and algorithms are proposedby researchers for invisible watermarking. In this paper, we focus on issuesthat are critical for security aspects in the most common domains like digitalphotography copyrighting, online image stores, etc. The requirements of thisclass of application include robustness (resistance to attack), blindness (directextraction without original image), high embedding capacity, high Peak Signalto Noise Ratio (PSNR), and high Structural Similarity Matrix (SSIM). Mostof these requirements are conflicting, which means that an attempt to maximizeone requirement harms the other. In this paper, a blind type of imagewatermarking scheme is proposed using Lifting Wavelet Transform (LWT)as the baseline. Using this technique, custom binary watermarks in the formof a binary string can be embedded. Hu’s Invariant moments’ coefficientsare used as a key to extract the watermark. A Stochastic variant of theFirefly algorithm (FA) is used for the optimization of the technique. Undera prespecified size of embedding data, high PSNR and SSIM are obtainedusing the Stochastic Gradient variant of the Firefly technique. The simulationis done using Matrix Laboratory (MATLAB) tool and it is shown that theproposed technique outperforms the benchmark techniques of watermarkingconsidering PSNR and SSIM as quality metrics.

A Novel Color Image Watermarking Method with Adaptive Scaling Factor Using Similarity-Based Edge Region

This study aimed to deal with three challenges:robustness,imperceptibility,and capacity in the image watermarking field.To reach a high capacity,a novel similarity-based edge detection algorithm was developed that finds more edge points than traditional techniques.The colored watermark image was created by inserting a randomly generated message on the edge points detected by this algorithm.To ensure robustness and imperceptibility,watermark and cover images were combined in the high-frequency subbands using Discrete Wavelet Transform and Singular Value Decomposition.In the watermarking stage,the watermark image was weighted by the adaptive scaling factor calculated by the standard deviation of the similarity image.According to the results,the proposed edge-based color image watermarking technique has achieved high payload capacity,imperceptibility,and robustness to all attacks.In addition,the highest performance values were obtained against rotation attack,to which sufficient robustness has not been reached in the related studies.

Quantization-Based Robust Image Watermarking Using the Dual Tree Complex Wavelet Transform

Conventional quantization index modulation (QIM) watermarking uses the fixed quantization step size for the host signal.This scheme is not robust against geometric distortions and may lead to poor fidelity in some areas of content.Thus,we proposed a quantization-based image watermarking in the dual tree complex wavelet domain.We took advantages of the dual tree complex wavelets (perfect reconstruction,approximate shift invariance,and directional selectivity).For the case of watermark detecting,the probability of false alarm and probability of false negative were exploited and verified by simulation.Experimental results demonstrate that the proposed method is robust against JPEG compression,additive white Gaussian noise (AWGN),and some kinds of geometric attacks such as scaling,rotation,etc.

A Feature-based Robust Digital Image Watermarking Against Desynchronization Attacks

In this paper, a new content-based image watermarking scheme is proposed. The Harris-Laplace detector is adopted to extract feature points, which can survive a variety of attacks. The local characteristic regions （LCRs） are adaptively constructed based on scale-space theory. Then, the LCRs are mapped to geometrically invariant space by using image normalization technique. Finally, several copies of the digital watermark are embedded into the nonoverlapped LCRs by quantizing the magnitude vectors of discrete Fourier transform （DFT） coefficients. By binding a watermark with LCR, resilience against desynchronization attacks can be readily obtained. Simulation results show that the proposed scheme is invisible and robust against various attacks which includes common signals processing and desynchronization attacks.

AN ADAPTIVE DIGITAL IMAGE WATERMARK ALGORITHM BASED ON GRAY-SCALE MORPHOLOGY

An adaptive digital image watermark algorithm with strong robustness based on gray-scale morphology is proposed in this paper.The embedded strategies include:The algorithm seeks and extracts adaptively the image strong texture regions.The algorithm maps the image strong texture region to the wavelet tree structures, and embeds adaptively watermark into the wavelet coefficients corresponding to the image's strong texture regions.According to the visual masking features, the algorithm adjusts adaptively the watermark-embedding intensity.Experimental results show the algorithm is robust to compression, filtering, noise as well as strong shear attacks.The algorithm is blind watermark scheme.The image strong texture region extraction method based on morphology in this algorithm is simple and effective and adaptive to various images.

Robust Image Watermarking Based on Generative Adversarial Network

Digital watermark embeds information bits into digital cover such as images and videos to prove the creator’s ownership of his work.In this paper,we propose a robust image watermark algorithm based on a generative adversarial network.This model includes two modules,generator and adversary.Generator is mainly used to generate images embedded with watermark,and decode the image damaged by noise to obtain the watermark.Adversary is used to discriminate whether the image is embedded with watermark and damage the image by noise.Based on the model Hidden(hiding data with deep networks),we add a high-pass filter in front of the discriminator,making the watermark tend to be embedded in the mid-frequency region of the image.Since the human visual system pays more attention to the central area of the image,we give a higher weight to the image center region,and a lower weight to the edge region when calculating the loss between cover and embedded image.The watermarked image obtained by this scheme has a better visual performance.Experimental results show that the proposed architecture is more robust against noise interference compared with the state-of-art schemes.

Difference Energy Based Blind Image Watermarking Resisting to Geometrical Distortions

In this paper a blind image watermarking that can resist to rotation, scaling and translation （RST） attacks is proposed. Based on the spread spectrum, the watermark is modulated before embedding. The logpolar mapped discrete fourier transform （LPM-DFT） magnitude of a disk, a part of the origin image, constitutes the RST-invariant domain, where the origin of the LPM is the center of the disk and the sampling rates of the LPM are constant. After the middle frequency band of LPM-DFT magnitude, namely the watermark-embedding domain, is grouped according to the watermark length, the watermark is embedded by adjusting the difference between the two sub-region energy in each group. To improve the imperceptibility, the watermark-embedding domain is shuffled before embedding and the watermark is not embedded directly into the watermark-embedding domain. In watermark detection procedure, neither the original image nor any knowledge about the distortions is required. Experimental results show that the proposed scheme is very robust against RST distortion and common image processing attacks.

New Optimal DWT Domain Image Watermarking Technique via Genetic Algorithm

A novel optimal image watermarking scheme is proposed in which the genetic algorithm (GA) is employed to obtain the improvement of algorithm performance. Arnold transform is utilized to obtain the scrambled watermark, and then the embedding and extraction of watermark are implemented in digital wavelet transform (DWT) domain. During the watermarking process, GA is employed to search optimal parameters of embedding strength and times of Arnold transform to gain the optimization of watermarking performance. Simulation results show that the proposed method can improve the quality of watermarked image and give almost the same robustness of the watermark.

Efficient gray-level digital image watermarking based on vector quantization

Digital watermarking has been presented as a new method for copyright protection by embedding a secret signal in a digital image or video sequence. Common digital image watermarking techniques are based on the concept of spread spectrum communications, which can be classified in two catalogues: spatial domain and transform domain based. Most of transform domain watermarking methods are based on discrete cosine transforms (DCT) and robust to JPEG lossy compression. Recently, digital image watermarking based on another important lossy compression technique, vector quantization (VQ), has been presented, which carries watermark information by codeword indices. It is secret and efficient, and is robust to VQ compression with the same codebook. However, the embedded information is less and the extraction process requires the original image. This paper presents a more efficient VQ based image watermarking method, which can embed a large gray level watermark into the original image with less extra distortion and perform the watermark extraction without the original image. In addition, the proposed watermarking algorithm is very secret because two keys are required for watermark extraction. Experimental results demonstrate the effectiveness of the proposed technique.

Wavelet Transform Modulus Maxima-Based Robust Digital Image Watermarking in Wavelet Domain

A new robust watermarking approach was proposed in 2D continuous wavelet domain （CWT）. The watermark is embedded into the large coefficients in the middle band of wavelet transform modulus maxima （WTMM） of the host image. After possible attacks, the watermark is then detected and extracted by correlation analysis. Compared with other wavelet domain watermarking approaches, the WTMM approach can endow the image with beth rotation and shift invariant properties. On the other hand, scale invariance is achieved with the geometric normalization during watermark detection. Case studies involve various attacks such as shifting, lossy compression, scaling, rotation and median filtering on the watermarked image, and the result shows that the approach is robust to these attacks.

Embedding Color Watermark Image into Color Host Image Based on Contourlet-Domain

A novel image blind watermarking scheme based on Contourlet transform was proposed to embed color watermark image into color host image, which was different from some existing works using the binary or gray-level image as watermark. In the process of embedding watermark, each color component of the color host image was decomposed by Contourlet transform. Then, the low-pass sub-band coeffidents were divided to 4 x 4 non-overlapping blocks, and the eoeffidents in the selected block were quantified for embedding the watermark information. In the process of extraction watermark, the watermark could be extracted from the watermarked image without the help of the original host image or the original watermark image. Experimental results show that the proposed color image scheme has better invisibility and stronger robustness against most attacks such as image compression, filtering, adding noise, cropping, rotation, and scaling.

Rotation,scaling and translation invariant image watermarking using feature points

In this article, a novel robust image watermarking scheme is presented to resist rotation, scaling, and translation （RST）. Initially, the original image is scale normalized, and the feature points are then extracted. Furthermore, the locally most stable feature points are used to generate several nonoverlapped circular regions. These regions are then rotation normalized to generate the invariant regions. Watermark embedding and extraction are implemented in the invariant regions in discrete cosine transform domain. In the decoder, the watermark can be extracted without the original image. Simulation results show that the proposed scheme is robust to traditional signal processing attacks, RST attacks, as well as some combined attacks.

Geometric attack resistant image watermarking based on MSER

Geometric distortions are simple and effective at- tacks rendering many watermarking methods useless. They make detection and extraction of the embedded watermark difficult or even impossible by destroying the synchroniza- tion between the watermark reader and the embedded water- mark. In this paper, we propose a blind content-based image watermarking scheme against geometric distortions. Firstly, the MSER detector is adopted to extract a set of maximally stable extremal regions which are affine covariant and robust to geometric distortions and common signal processing. Sec- ondly, every original MSER is fitted into an elliptical region that was proved to be affine invariant. In order to achieve rota- tion invariance, an image normalization process is performed to transform the elliptical regions into circular ones. Finally, watermarks are repeatedly embedded into every circular disk by modifying the wavelet transform coefficients. Experimen- tal results on standard benchmark demonstrate that the pro- posed scheme is robust to geometric distortions as well as common signal processing.

A robust color image watermarking algorithm against rotation attacks

A robust digital watermarking algorithm is proposed based on quaternion wavelet transform(QWT) and discrete cosine transform(DCT) for copyright protection of color images. The luminance component Y of a host color image in YIQ space is decomposed by QWT, and then the coefficients of four low-frequency subbands are transformed by DCT. An original binary watermark scrambled by Arnold map and iterated sine chaotic system is embedded into the mid-frequency DCT coefficients of the subbands. In order to improve the performance of the proposed algorithm against rotation attacks, a rotation detection scheme is implemented before watermark extracting. The experimental results demonstrate that the proposed watermarking scheme shows strong robustness not only against common image processing attacks but also against arbitrary rotation attacks.

Modified Moment-based Image Watermarking Method Robust to Cropping Attack

Developing a watermarking method that is robust to cropping attack is a challenging task in image watermarking. The moment-based watermarking schemes show good robustness to common signal processing attacks and some geometric attacks but are sensitive to cropping attack. In this paper, we modify the moment-based approach to deal with cropping attack. Firstly, we find the probability density function （PDF） of the pixel value distribution from the original image. Secondly, we reshape and normalize the pdf of the pixel value distribution （PPVD） to form a two dimensional image. Then, the moment invariants are calculated from the PPVD image. Since PPVD is insensitive to cropping, the proposed method is robust to cropping attack. Besides, it also has high robustness against other common attacks. Theoretical analysis and experimental results demonstrate the effectiveness of the proposed method.

A New Technique for Digital Image Watermarking

In this paper, a new technique is proposed for rotation, scaling and translation （RST） invariant image watermarking based on log-polar mappings （LPM） and phase-only filtering （POF）. The watermark is embedded in the LPM of Fourier magnitude spectrum of the original image, and a small portion of resulting LPM spectrum is used to calculate the watermark positions. This technique avoids computing inverse log-polar mapping （ILPM） to preserve the quality of the watermarked image, and avoids exhaustive search to save computation time and reduce false detection. Experimental results demonstrate that the digital watermarking technique is invariant and robust to rotation, scaling, and translation transformation.

Geometrically invariant color image watermarking scheme using feature points

Geometric distortion is known as one of the most difficult attacks to resist. Geometric distortion desynchronizes the location of the watermark and hence causes incorrect watermark detection. In this paper, we propose a geometrically invariant digital watermarking method for color images. In order to synchronize the location for watermark insertion and detection, we use a multi-scale Harris-Laplace detector, by which feature points of a color image can be extracted that are invariant to geometric distortions. Then, the self-adaptive local image region （LIR） detection based on the feature scale theory was considered for watermarking. At each local image region, the watermark is embedded after image normalization. By binding digital watermark with invariant image regions, resilience against geometric distortion can be readily obtained. Our method belongs to the category of blind watermarking techniques, because we do not need the original image during detection. Experimental results show that the proposed color image watermarking is not only invisible and robust against common signal processing such as sharpening, noise adding, and JPEG compression, but also robust against the geometric distortions such as rotation, translation, scaling, row or column removal, shearing, and local random bend.