Original Watermark Image Research Articles

A secure fractional-order polar harmonic transforms based image watermarking scheme using funk singular value decomposition

In addition to existing cryptographic systems, watermarking technologies have been developed to add extra security. Digital watermarking utilizes embedding or hiding techniques to protect multimedia files from copyright violations. Fundamental procedures of digital watermarking techniques are embedding and extraction. Singular value decomposition (SVD) based Image watermarking schemes become popular owing to its better trade-off among robustness and imperceptibility. Nevertheless, false positive problem (FPP) is a major issue of SVD-based watermarking schemes. The singular value that is a fixed value and does not contain structural information about image is the primary cause of FPP problem. Therefore, Message Digest algorithm image watermarking scheme based on Funk Singular Value Decomposition and Fractional-Order Polar Harmonic Transform (FSVD-FOPHT) is proposed in this paper to address this problem. The MD-5 algorithm is used to extract data from the host and watermark imageries and then create secret key. The FSVD-FOPHT method is utilized to hide watermark information in host image. The secret keys are extracted from hided image using inverse process of Fractional-Order Polar Harmonic Transforms with Funk Singular Value Decomposition algorithm. By using the extraction procedure, watermark image is extracted, and then reconstructs original watermarked image. During extraction procedure, the secret key is used for authentication to address FPP. Then, the proposed method is implemented in MATLAB and performance is analyzed with evaluation metrics, such as Embedding capacity, MSE, PSNR, and NC. The proposed method provide 14.6%, 17.34%, 19.53%, 21.46% and 23.89% high PSNR for cold-snow-landscape-water test image, 14.29%, 16.47%, 18.39%, 20.16% and 21.93% high PSNR for landscape-nature-sky-blue Test image, 16.85%, 19.99%, 22.70%, 27.22% and 29.16% high Embedding Capacity for cold-snow-landscape-water test image 22.83%, 24.64%, 27.92%, 29.60% and 31.77% high Embedding Capacity for landscape-nature-sky-blue Test image 35.38%, 32.63%, 30.95%, 28.61% and 26.08% low extraction time compared with existing methods SVD-CMSF-SIW, FE-IWS-DNN, AR-IWS-DNN, BBET-SHA1-SIW and LSB-DWT-SIW respectively.

A Quantum Image Watermarking Scheme Based on Quantum Hilbert Scrambling and Steganography about the Moiré Fringe

In order to boost the security and confidentiality of information in quantum images, on the foundation of the NEQR model, a novel quantum watermarking scheme combining quantum Hilbert scrambling with steganography based on the Moiré fringe is designed in this paper. First of all, for carrier image, and watermark image, the color information and position information are denoted, respectively, by the NEQR model. Next, the watermark image is converted to a disordered image by quantum Hilbert scrambling, and the message of the original watermark image cannot be gained from the disordered image. At last, the watermark image after scrambling is embedded into the carrier image through the steganography of the Moiré fringe, obtaining the watermarked image. Due to the unitary image of the quantum gate, quantum Hilbert inverse scrambling is the opposite process of quantum Hilbert scrambling. In addition, the watermark image can be completely extracted from the watermarked image. What’s more, the experimental simulation and performance analysis of the scheme are done. The experimental simulation proves the feasibility of this algorithm. Visually, there is no difference between the carrier image and the watermarked image. The PSNR between the watermarked image and the carrier image is measured, which quantitatively shows the high similarity. In addition, the time complexity of the quantum circuit is lower than some other quantum image watermarking schemes, which proves the simplicity of this scheme.

Robust dual color images watermarking scheme with hyperchaotic encryption based on quaternion DFrAT and genetic algorithm

A robust dual color images watermarking algorithm is designed based on quaternion discrete fractional angular transform (QDFrAT) and genetic algorithm. To guarantee the watermark security, the original color watermark image is encrypted with a 4D hyperchaotic system. A pure quaternion matrix is acquired by performing the discrete wavelet transform (DWT), the block division and the discrete cosine transform on the original color cover image. The quaternion matrix is operated by the QDFrAT to improve the robustness and the security of the watermarking scheme with the optimal transform angle and the fractional order. Then the singular value matrix is obtained by the quaternion singular value decomposition (QSVD) to further enhance the scheme’s stability. The encryption watermark is also processed by DWT and QSVD. Afterward, the singular value matrix of the encryption watermark is embedded into the singular value matrix of the host image by the optimal scaling factor. Moreover, the values to balance imperceptibility and robustness are optimized with a genetic algorithm. It is shown that the proposed color image watermarking scheme performs well in imperceptibility, security, robustness and embedding capacity.

Zero-Watermarking Algorithm for Remote Sensing Image via BEMD and DFT

In order to solve the problem of modifying the host image when the traditional image watermarking algorithm protects the copyright of remote sensing image, and to improve the robustness of remote sensing image watermarking algorithm, a remote sensing image zero watermarking algorithm based on bi-dimensional empirical mode decomposition (BEMD) and discrete Fourier transform (DFT) is proposed. Firstly, BEMD is used to decompose the host image to get the intrinsic mode function and margin, and the residual information is divided into 8×8 blocks DFT, and the high frequency coefficients are constructed into coefficient images. Then Arnold transform is used to scramble the watermark image to improve the security of the watermark image. Then the size of the watermark image is adjusted to solve the problem of image size matching between the host image and the watermark image in the process of watermark embedding. Finally, the coefficient image decomposed by DFT and the watermark image are constructed into feature image by XOR operation, and the construction of zero watermark in remote sensing image is realized. The experimental results of a large number of remote sensing images and watermark images show that the proposed algorithm can effectively resist all kinds of attacks such as filtering, sharpening, histogram equalization, Gamma transform, noise, scaling and so on. In the case of 12 attacks and 60 parameters, 95.0% of the extracted watermark images have a normalized correlation value of more than 0.990 with the original watermark image, compared with the traditional remote sensing image watermarking algorithm. The algorithm ensures the harmlessness of the host image, so that the feature image saved in the notary office for copyright protection verification will not cause any damage to the host image, and has better robustness.

A Novel Invariant Based Commutative Encryption and Watermarking Algorithm for Vector Maps

Commutative encryption and watermarking (CEW) is an emerging method that combines encryption technology with digital watermarking technology. It has the dual capability of secure transmission and copyright protection. However, the existing CEW methods for vector maps have good robustness in resisting geometric attacks but poor resistance to vertex attacks (e.g., addition, deletion, etc.). To solve this problem, here we propose a novel invariant-based CEW algorithm for vector maps, which consists of permutation-based encryption scheme and coordinates-based watermarking scheme. In the encryption scheme, the encryption key is generated via the Gaussian distribution method combined with the SHA-512 hash method; then, the double random position permutation strategy is applied to the vector map encryption. In watermarking embedding scheme, the original watermark image is scrambled via logistic chaotic encryption before embedding, and the coordinates of all the vertices are normalized. Then, the scrambled watermark image is embedded into the normalized coordinates. Results show that: proposed method is more robust to conventional attacks (e.g., vertex addition and deletion, reordering and data format conversion) and geometric attacks (e.g., scaling and translation). In addition, compared with the existing CEW methods for vector maps, the proposed method has higher security and stronger robustness against vertex attacks.

A Zero-Watermark Hybrid Algorithm for Remote Sensing Images Based on DCT and DFT

Remote sensing image has significant advantages such as large detection range and fast acquisition speed, so it has been used in military, environmental, meteorological and other fields. In order to improve the robustness of the digital watermarking technology on the premise that the remote sensing image information is not modified, a remote sensing image zero watermarking algorithm based on Discrete Cosine Transform (DCT) and Discrete Fourier Transform (DFT) is proposed in this paper. First of all, the color remote sensing image is converted into grayscale image. The transformed coefficient matrix is obtained by DFT, to the grayed host image. Secondly, in order to compress the amount of information and improve the efficiency of the algorithm, the high frequency coefficient image is transformed by DCT transform. The low frequency coefficient image which is consistent with the size of the watermark image after DCT is selected as the feature image of the host image. After that, the watermark information is scrambled by Arnold transform to improve the security of the watermark information. Finally, the zero-watermark image is obtained by XOR operation between the scrambled watermark information and the feature image. The zero-watermark image is saved in a third-party database for copyright verification. In order to verify the robustness of digital watermarking, this paper carries out sharpening, histogram equalization, Karma transform, noise, filtering and geometric attacks on the host image, and compares it with other algorithms. The NC value between the extracted watermark image and the original watermark image after attacking the host image show that the algorithm has a strong ability to resist common attacks.

Single Exposure Optical Image Watermarking Using a cGAN Network

A single exposure optical image watermarking framework based on deep learning (DL) is proposed in this paper, and original watermark image information can be reconstructed from only single-frame watermarked hologram by using an end-to-end network with high-quality. First, the single exposure watermarked hologram is acquired with our presented phase-shifted interferometry based optical image watermarking (PSOIW) frame, and then all holograms and corresponding watermark images are constructed to the train datasets for the learning of an end-to-end conditional generative adversarial network (cGAN), finally retrieved the watermark image well with the trained cGAN network using only one hologram. This DL-based method greatly reduces the recording or transmitting data burden by 1/4 compared with our presented PSOIW technique, and may provide a new way for the real-time 3D image/video security applications. The feasibility and security of the proposed method are demonstrated by the optical experiment results.

Research on Reversible Visible Watermarking Algorithms Based on Vectorization Compression Method

Abstract In current research on reversible visible watermarking algorithm, the original visible watermark image plays an important auxiliary role, and some algorithms also entirely depend on it to restore host image without any distortion. Therefore, in order to realize semi-blind reversible visible watermarking algorithm, the conventional reversible watermarking algorithm is used to embed compressed visible watermark image data into non-visible-watermarked region of host image. However, the amount of compressed image data obtained by conventional image compression algorithm is relatively large. Therefore, a method based on vectorization compression for the visible watermark image is proposed in this paper. Firstly, it performs edge detection on visible watermark image to obtain a discrete points set $\Gamma $ of vector contour curve. Then, the discrete points in $\Gamma $ are simplified by improved Douglas–Peucker algorithm, after that it obtains compressed vector contour data of visible watermark image. In addition, a reversible visible watermarking algorithm based on convolutional relief and image alpha fusion is proposed, which realizes reversible embedding of visible watermark image and lossless restoration of host image. The experimental results show that the proposed vectorization compression method has more advantages than traditional image compression algorithms, which greatly reduces the storage space of visible watermark image with high fidelity. Additionally, the embedded watermarking image has translucent 3D relief effect, and the fusion of host image and visible watermark image becomes more natural and harmonious.

Information hiding algorithm based on edge detection and holographic watermarking

In order to improve the robustness of the image watermarking and reduce the influence of the overall image quality of the carrier when watermark is embedded on the carrier, an edge detection method combined with holographic watermarking was proposed to realize the hiding of watermark information. The carrier image is processed by edge detection, the watermark embedding area is segmented in the carrier image, and the suitable embedding area is filtered according to the size of the watermark; the original watermark is processed by a four-step phase shift algorithm to generate a holographic watermark, and the holographic watermark is embedded in the selection The embedding area is completed to embed the watermark, and the carrier image which the watermark is embedded in is carrier image with watermark. The watermark extraction method is to perform the same edge detection segmentation and region screening on the watermark carrier image, find the embedded area of the watermark, extract the holographic watermark, perform holographic inverse transformation to obtain the original watermark image, and complete the watermark recovery. The algorithm which is based on edge detection and holographic watermarking reduces the influence of embedded watermark on the carrier image, increases the flexibility and concealment of embedded position, and improves the robustness of the image when it is under geometric attacks.

Hybrid watermarking scheme based on singular value decomposition ghost imaging

A hybrid watermarking algorithm with an optical watermark image based on singular value decomposition (SVD) ghost imaging is designed. Simultaneously, the blended watermarking algorithm is designed based on 4-level discrete wavelet transform (DWT), discrete cosine transform (DCT) and singular value decomposition (SVD). The 4-level diagonal sub-band image is obtained by performing 4-level two-dimensional wavelet transform on the original image, and the coefficient matrix is produced by applying the discrete cosine transform on the 4-level diagonal sub-band image. Then, three matrices are obtained by performing the singular value decomposition on the coefficient matrix. In addition, the optical watermark image is encrypted by an SVD ghost imaging system. The system could generate a secret key, and unauthorized users could not decrypt and reconstruct the original watermark image without this key. Later the encrypted watermark image is generated into the other three matrices by singular value decomposition. Afterwards, the encrypted watermark is embedded in the host image by mutual operation of different matrices in the algorithm. Simulation results validate the feasibility of the proposed hybrid watermarking scheme.

A hybridized methodology of different wavelet transformations targeting medical images in IoT infrastructure

The Internet of Things (IoT) paradigm has become a vital part of all significant scientific sectors, including the healthcare domain. Medical images in the healthcare sector are indispensable items that are usually susceptible to distortion once they are shared and transferred via the Internet. The sector faces the distinct and constant challenge of preserving medical data, which can be manipulated by various malicious attacks, in turn potentially compromising the patients’ diagnostic data. In this situation, such medical data ought to be private, with access only granted to patients and physicians. This paper elaborates on a hybrid measurement technique for digital image watermarking that utilizes medical images (X-ray, MRA, and CT), which are an extremely robust method for protecting clinical information. The authors explore various different wavelet families, in addition to hybridization between these wavelets. These are carried out on three levels decomposition of Discrete wavelet transformation (biorthogonal 6.8 wavelets, biorthogonal 3.5 wavelets, biorthogonal 5.5 wavelets, reverse biorthogonal 6.8, reverse biorthogonal 3.5, reverse biorthogonal 5.5, discrete meyer, symlets 5, symlets 8 coiflets 4 wavelet, and coiflets 5 wavelet transform). Each level uses various types of wavelet transformation to present the watermarked image, and then extracts the medical watermark from the original watermarked image. The results of diverse types of attack have been compared, while the proposed measurement technique's performance is evaluated using statistical parameters (MSE, PSNR, SSIM, and NC). This in turn measures the quality of the image, which so far shows promising results.

Optical image watermarking based on singular value decomposition ghost imaging and lifting wavelet transform

An optical image watermarking method based on singular value decomposition ghost imaging (SVDGI) and a blind watermarking algorithm is proposed. The watermark image is first encrypted by an SVDGI system, then the encrypted watermark is embedded in the host image with the help of the watermark algorithm, which uses the block discrete cosine transform (DCT) and integer lifting wavelet transform (LWT). The proposed watermarking algorithm has good imperceptibility and robustness, and no original host image is needed when extracting the watermark. SVDGI provides a new reconstruction method in ghost imaging (GI) by modifying the measurement matrix with the help of singular value decomposition, which carries out the reconstruction process in less time and at higher quality. The measurement matrix composes a secret key, and only with this key can authorized users decrypt and reconstruct the original watermark image. Both optical experiments and numerical simulations validate the feasibility of the proposed method.

Quantum color image watermarking based on fast bit-plane scramble and dual embedded

Most of the studied quantum encryption algorithms are based on square images. In this paper, based on the improved novel quantum representation of color digital images model (INCQI), a quantum color image watermarking scheme is proposed. First, INCQI improved from NCQI is used to represent the carrier and watermark images with the size [Formula: see text] and [Formula: see text], respectively. Secondly, before embedding, the watermarking needs to be preprocessed. That is, the watermark image with the size of [Formula: see text] with 24-qubits color information is disordered by the fast bit-plane scramble algorithm, and then further expanded to an image with the size [Formula: see text] with 6-qubits pixel information by the nearest-neighbor interpolation method. Finally, the dual embedded algorithm is executed and a key image with 3-qubits information is generated for retrieving the original watermark image. The extraction process of the watermark image is the inverse process of its embedding, including inverse embedding, inverse expand and inverse scrambling operations. To show that our method has a better performance in visual quality and histogram graph, a simulation of different carrier and watermark images are conducted on the classical computer’s MATLAB.

A Study of Digital Image Watermarking for JPEG and PNG Images using Discrete Wavelet Transform

Objectives: To emphasis on digital image watermarking techniques and its applications using Discrete Wavelet Transform (DWT). Methods: We propose two watermarking algorithms for embedding and extraction process and use two images as cover image and watermark image of same format as input image. We have considered two image formats JPEG (Joint Photographic Experts Group) and PNG (Portable Network Graphics) of different resolutions for analyzing the performance of the proposed algorithm. Findings: The proposed research work is compared with the existing works on the basis of compression percentage, MSE (Mean Square Error), PSNR (Peak Signal to Noise Ratio) and Normalized Correlation (NC) values and the result has been carried out using DWT in Matlab 7.12. All the existing watermarking techniques referred in this paper have some limitations at somewhere. The PSNR values of all the existing research works is not more than 50 dB for the entire traditional image processing images. But in this proposed research work, the PSNR value is more than 66 dB for all the twenty test images we have taken. Higher the PSNR value means the quality of the watermark image is better. If the PSNR value is good then the MSE value will automatically be good because one is inversely proportional to other. Improvements: In the previous research works, common values of PSNR were between 30 dB to 50 dB. If the PSNR value of the watermark image is more than 50 dB then it will be tough to detect the difference between the cover image and the watermark image by the common Human Visibility System (HVS). The NC value 1 means that the correlation between the extracted watermark image and the original watermark image is almost similar in a particular point.

Novel blind colour image watermarking technique using Hessenberg decomposition

In this study, a novel blind image watermarking technique using Hessenberg decomposition is proposed to embed colour watermark image into colour host image. In the process of embedding watermark, the watermark information of colour image is embedded into the second row of the second column element and the third row of the second column element in the orthogonal matrix obtained by Hessenberg decomposition. In the process of extracting watermark, neither the original host image nor the original watermark image is needed and it is impossible to retrieve them without the authorised keys. Experimental results show that the proposed colour image watermarking technique based on Hessenberg decomposition outperforms other watermarking methods and it is robust to resist a wide range of attacks, e.g. image compression, filtering, cropping, rotation, adding noise, blurring, scaling, sharpening and rotation and so on. Especially, the proposed method has lower computational complexity than other methods based on singular value decomposition or QR decomposition.

A New Zero-Watermarking Algorithm Resisting Attacks Based on Differences Hashing

Abstract Medical volume data containing patient information is often faced with various attacks in the transmission process. In order to enhance the medical information system security, and effectively solve the problem of medical volume data protection, a new zero-watermarking algorithm is proposed in the paper. The new zero-watermarking algorithm takes advantage of three-dimensional discrete wavelet transform multi-resolution analysis characteristics of space and time, threedimensional discrete cosine transform properties, and differences hashing robust characteristic. In order to enhance watermarking algorithm security, Legendre chaotic neural network is used for scrambling original watermark image. The medical volume data is made by three-dimensional discrete wavelet transform, threedimensional discrete cosine transform and three-dimensional discrete inverse cosine transform r to obtain the medical volume data feature matrix (4×5×4), which is converted to 64-bit binary feature sequence through difference hashing algorithm. The 64-bit binary feature sequence is used to construct the zero-watermarking. The experimental results prove that the new zero-watermarking has favorable security and robustness resisting various attacks. Therefore, the new zero-watermarking algorithm is more applicable to protect medical volume data.

Frequency domain digital watermark recognition using image code sequences with a back-propagation neural network

Digital watermarking is an encryption technique commonly used to protect intellectual property and copyright. Although watermarks are a robust method of protecting property rights, environmental interference in image propagation through the Internet is inevitable, and human-based image modification can also destroy watermarks. In this study, watermarks (affected by noise interference) were embedded in a 256ź×ź256 pixel host image by using the discrete cosine transform (DCT) technique, which transfers the spatial domain of the host image into the frequency domain. Subsequently, 32ź×ź32 pixel watermarked images were embedded as watermark identification codes in the transferred frequency-domain-based host image. The inverse discrete cosine transform (IDCT) technique was used to alter the frequency of the spatial domain, thereby allowing the host image to be visible to the human eye. Several common interferences, such as salt-and-pepper noise, Gaussian noise, clipping, and rotation, were used to destroy the watermarked image. After the destruction process, the watermark was almost discernible in a slightly damaged state, but difficult to identify in a seriously damaged state after using the DCT watermarking scheme. In this study, a back-propagation neural network (BPNN) algorithm combined with a DCT watermarking scheme was used to suppress the interference affecting watermarks. The simulation results of using the proposed DCT-BPNN method indicated that the original watermarked image was restored considerably after being subjected to environmental interference during image propagation.

An Anti-cropping Watermarking Method for Facial Images Using Prediction and Weber Ratio Techniques

When a digital facial image is published in any social network, often the facial part of the image is cropped and abused without the owner permission. It is extremely difficult to verify the owner, especially in cases where the embedded watermark does not cover the cropped face part. This paper proposes a digital image watermarking method that is robust against cropping attack in the spatial domain for protecting the copyright of facial images. The face region in an image is evaluated by using phase correlation technique for embedding the watermark. A binary watermark is defined to be embedded in the facial region. Pixels for embedding the watermark are predicted and altered based on the Weber ratio to control the strength of the watermark in order to make it imperceptible to the human eye. The watermark is extracted from the watermarked image that does not require the original image by subtracting the watermarked pixel from its predicted pixel. After this, the pieces of the extracted watermarks are verified to measure their similarity with the original watermark. The experimental results show that our method yielded 82 % similarity with the original watermark image, when it was attacked by the cropping attacks for any shapes, sizes, locations and the JPEG compression.

Encoded Hybrid DWT based Watermarking Scheme based on Singular Matrix Decomposition

In the period of digital technology, digital information suffers from copyright and integrity violations. In case of any disputes like rights violation and content creator, digital watermark has a vital role to protect the property rights of the original owner of digital information. Numerous of watermarking techniques have been proposed recently but image quality of host image at receiving end is needed to be improved. We proposed Encoded Hybrid Digital Watermarking Scheme (EHDWS) to improve image quality which is based on Discrete Wavelet Transform (DWT), Singular Value Decomposition (SVD) and Bose ChaudhuriHocquenghem (BCH) code. DWT is used for decomposing the image into LL, HL, LH, HH sub-bands; SVD is used to decompose the image into orthogonal matrix (U), singular matrix (S), and inverse orthogonal matrix (V) and BCH code is used for error detection-correction, copyright protection and authentication. The proposed EHDWS has high degree of transparency, robustness, blindness. In EHDWS, watermark embedding scheme is used to encode the original watermark image by using BCH (7, 4) based algorithm for obtaining the encoded watermark image. Then embed this encoded watermark image into host image by using DWT-SVD based algorithm for obtaining the watermarked image. Watermark extracting scheme is used to obtain both extracted watermark image for authentication purpose and extracted host image from watermarked image to obtain original image. PSNR values are also calculated to know the quality of watermarked image. General Terms Image security, watermarking.

An Adaptive Color Image Visible Watermark Algorithm Supporting for Interested Area and its Application System Based on Internet

This paper presents an interested area visible watermark algorithm for digital color image based on internet. By converting color image from RGB to HSI and using the original image information to obtain the watermark coefficient, the algorithm embeds watermark on the spatial domain and selects the interested area by clicking on the picture. By visiting the site (http://dgdz.ccee.cqu.edu.cn/watermark/watermarkb.aspx) and uploading the original image and watermark image, the color image with the visible watermark can be gained on web. Experimental results show that the algorithm has only a little influence on the original image and the image of watermark is clearly visible. It is very suitable for obvious identification of the copyright from digital image through Internet.