Extracted Watermark Image Research Articles

A strategy for quantum watermarking against geometric attacks

The development of new quantum watermarking is in full swing, and it is crucial to test the robustness of these proposed watermarking schemes. In this paper, different quantum circuits are introduced to realize geometric transformations on quantum images, which serve as a means of simulating geometric attacks on quantum watermark images. Receivers may get distorted images, and the extracted watermark images may also be disrupted. To recover the geometric order of the quantum watermark images, a strategy is proposed to identify the trajectory of qubit alterations. Quantum circuits can be designed accordingly to restore the original order of the watermark images, which receivers could use before the extraction process to mitigate the impact of geometric attacks. Experimental simulations demonstrate how attacks affect the quantum watermark images and the extracted watermark images. Additionally, it illustrates how quantum recovery circuits step by step act on images that have been geometrically attacked. An analysis of the complexity of geometric restoration circuits reveals that quantum circuits exhibit better performance compared to classical circuits.

Robust Watermarking Using FFT and Cordic QR Techniques

Digital media sharing and access in today’s world of the internet is very frequent for every user. The management of digital rights may come into threat easily as the accessibility of data through the internet become wide. Sharing digital information under security procedures can be easily compromised due to the various vulnerabilities floating over the internet. Existing research has been tied to protecting internet channels to ensure the safety of digital data. Researchers have investigated various encryption techniques to prevent digital rights management but certain challenges including external potential attacks cannot be avoided that may give unauthorized access to digital media. The proposed model endorsed the concept of watermarking in digital data to uplift media security and ensure digital rights management. The system provides an efficient procedure to conduct over-watermarking in digital audio signals and confirm the avoidance of ownership of the host data. The proposed technique uses a watermark picture as a signature that has been initially encrypted with Arnold's cat map and cyclic encoding before being embedded. The upper triangular R-matrix component of the energy band was then created by using the Fast Fourier transform and Cordic QR procedures to the host audio stream. Using PN random sequences, the encrypted watermarking image has been embedded in the host audio component of the R-matrix. The same procedure has been applied to extract the watermark image from the watermarked audio. The proposed model evaluates the quality of the watermarked audio and extracted watermark image. The average PSNR of the watermarked audio is found to be 37.01 dB. It has also been seen that the average PSNR, Normal cross-correlation, BER, SSMI (structure similarity index matric) value for the extracted watermark image is found to be 96.30 dB, 0.9042 units, 0.1033 units, and 0.9836 units respectively. Further, the model has been tested using various attacks to check its robustness. After applying attacks such as noising, filtering, cropping, and resampling on the watermarked audio, the watermark image has been extricated and its quality has been checked under the standard parameters. It has been found that the quality of the recovered watermark image satisfying enough to justify the digital ownership of the host audio. Hence, the proposed watermarking model attains a perfect balance between imperceptibility, payload, and robustness.

Non-redundant shift-invariant complex wavelet transform and fractional gorilla troops optimization-based deep convolutional neural network for video watermarking

With the development of multimedia processing approaches along with the Internet leads to various issues, like data tampering, data piracy, and illicit dissemination. The quick progression of fast communication networks for digital video transmission has formulated the prerequisite copyright protection for these media. On the other hand, the development of Internet technologies has directed the accessibility of images, audio, and videos in different structures. Moreover, unlicensed users manipulate the utilization of multimedia by broadcasting them on numerous internet sites to get money fraudulently without the involvement of the original copyright holder. Besides, watermarking is a process utilized to hide the watermark sign present in the multimedia statistics that are not perceptible to an intruder for manipulating any information. This paper devised a novel video watermarking technique which uses an optimized deep learning technique. Here, the binary pixel map generation is performed using DCNN for self-embedding in input video. In addition, weights as well as bias of DCNN are trained by designed Fractional Gorilla Troops Optimization-Deep Convolutional Neural Network algorithm, thus FGTO_DCNN algorithm is developed. Accordingly, the FGTO technique is newly introduced by integrating FC along with GTO algorithm. Moreover, non-redundant Shift Invariant Complex Wavelet Transform (SICWT) is employed for extracted key frame and thus watermark image is fed into embedding process. After that, inverse non-redundant SICWT is applied for embedding video, which is further passed to key frame extraction in extraction stage. Finally, non-redundant SICWT is utilized for obtaining extracted watermark image. The developed FGTO-driven DCNN model attained improved performance than other existing video watermarking techniques with Mean Square Error (MSE) of 0.0437, Normalized Correlation Coefficient (NCC) of 0.9998, high Peak Signal-to-Noise Ratio (PSNR) value of 51.93 dB, and high Weighted Signal-to-Noise Ratio (WSNR) of 49.86 dB.

Compression Run Length Encoding On Watermarking Using a Combination of DCT, DWT and SVD

This study focus on identifying medical images by proposing the Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT) and Singular Value Decomposition (SVD) transformation watermarking technique and prove an increase the quality of watermarked images is good in terms of imperceptibility. Due to reduce the need for data memory compression is applied to the host image, where the compression technique chosen is lossless so that the compressed host image experiences a decrease in file size while maintaining data integrity, to maintain image degradation perceptions and diagnostic quality standards during the watermarking process. Here, we use DWT-DCT-SVD and Run Length Encoding (RLE). A good Peak Signal to Noise Ratio (PSNR) more than 30 dB using over than 200 compression size. The extracted watermark image is quite good with a fairly high PSNR value. The highest compression result size is in 32.2511.

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.

Multi-image Feature Map-Based Watermarking Techniques Using Transformer

Nowadays, protecting multimedia data is a significant challenge because of the advancement of technology and software. The embedding process heavily relies on watermarking to accomplish multimedia security in terms of content authentication, proof of ownership, and tamper detection. Our objective is to develop an invariant watermark that can survive different signal-processing attacks. We presented a unique hybrid technique (DWT-QR-SWT) and multi-image invariant features generated as a watermark using a Transformer encoder-decoder model. The encoded image features are subsampled using PCA in order to decrease the dimensionality of the watermark image. The first two images are used as watermark1 and the next two images as watermark2 to produce multi-watermark feature maps. To embed the watermark, a hybrid DWT-QR decomposition has been applied to the original image1. On the primary watermarked image, two Level Stationary Wavelet Transform (SWT) were applied to embed the secondary watermark2. At the extraction phase, the tampered image is recovered by passing the extracted watermark image as input to the transformer decoder. A multi-image watermark increases data embedding capabilities and also achieves two-level content authentication, tamper detection, localization, and recovery. With a PSNR of 59.05 dB, the testing result demonstrates great resilience and improved imperceptibility.

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 Hybrid Digital Image Watermarking Scheme Incorporating DWT, DFT, DCT and SVD Transformations

Digital watermarking provides copyright protection and proof of ownership by inserting watermark metadata as owner’s identity in digital documents to prevent authenticity and copyright violations. The paper introduces a new hybrid image watermarking scheme by attaching multiple copies of watermarks in carrier image. The new scheme utilizes the advantages of DWT, DFT, DCT and SVD transformations to offer stable resistance in protecting watermark contents from various external attacks. The proposed scheme uses Haar wavelet, Fourier, Onion Peel Decomposition, DCT, zigzag ordering and SVD transforms to decompose the carrier image in to four levels to maintain imperceptibility in the watermarked images. The algorithm attaches replicas of watermark frequency blocks in all frequency components of host image to provide better robustness against external deprivations in watermarked images. The proposed algorithm also provides the increased probability of extracting at least one undamaged replica of watermark even when other frequencies are damaged by external attacks. The improved experimental results of the proposed scheme in terms of visual analysis and quantitative metrics on different images with different experimental set up demarcate that the proposed watermarking scheme provides stable performance in generating better watermarked images. It is experimentally found that the new scheme produces high quality watermarked images with an average of 7.62% lesser Mean Absolute Error (MAE) and increased Peak Signal to Noise Ratio (PSNR), Mean Structural Similarity Index Measure (MSSIM) and Feature Similarity Index Measure (FSIM) of 5.02 %, 4.37 %, and 2.37 % respectively than the next best algorithms when simulated with 20 sets of watermark and cover images. The watermark images extracted by the proposed algorithm from extremely distorted watermarked images are with better visual and objective values than other methods used in the comparative study. Simulation analysis on 20 sets of watermark and cover images with 30 types of potential attacks reveals that the extracted watermark images through the proposed scheme produces an average of 5.62%, 6.37%, 5.75% improved Pearson Correlation Coefficients (PCC), Number of Changing Pixel Rate (NPCR) and the Unified Averaged Changed Intensity (UACI) values respectively than the next best algorithms used in the comparative study.

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.

An adaptive, secure and imperceptive image watermarking using swarm intelligence, Arnold transform, SVD and DWT

Digital image watermarking is one of the important method of copyright protection and rightful ownership of the digital image and video. In this paper, the existing algorithm based on DWT-SVD is improved and made adaptive with particle swarm optimization (PSO) which increases the robustness and imperceptibility. Existing as well as proposed algorithm based on PSO creates diagonal line in the extracted watermark image against some of the noise attacks. Further to remove diagonal line from the extracted watermark image an algorithm based on PSO and Arnold transform is proposed. Both proposed algorithms (PSO and AT-PSO) are implemented and tested with different types of cover images. The comparative analysis of these two proposed algorithms is carried out with the existing algorithm. The comparative analysis shows that under most of noise attacks both the proposed algorithms outperform over the existing algorithm in terms of Peak Signal to Noise Ratio (PSNR) and Normalized Similarity Ratio (NSR). Moreover, the imperceptibility offered by Arnold transform based algorithm is better as compared to the other proposed algorithm. Robustness of both the proposed algorithms is close to each other.

An Optimized Hybrid Algorithm for Blind Watermarking Scheme Using Singular Value Decomposition in RDWT-DCT Domain

Watermarking is a technique which offers more robustness and good imperceptibility. Even if the algorithmic principle is public or the existence of hidden information is known, it is difficult to attacker to destroy the embedded watermark without degrading the watermarked media severely. In existence, non-blind watermarking (NBW) schemes and different combinations of techniques are proposed for watermarking procedure. But these methods failed to provide the good imperceptibility, lack of robustness and embedding capacity standards, respectively. Thus, to overcome this problem, a hybrid algorithm for blind watermarking (BW) is proposed, which utilizes redundant discrete wavelet transform (RDWT), discrete cosine transform (DCT) and singular value decomposition (SVD) together to have the advantages of all three. In addition, optimization of proposed RDWT-DCT-SVD is obtained using a new bio-inspired algorithm called Porcellio Scaber algorithm (PSA). Thus, the visual perception of extracted watermark image also good enough by maintaining the robustness against various image attacks. Experiments are carried out to test the proposed BW algorithm and it is successful under various geometrical and non-geometrical attacks. Finally, the performances of proposed BW using RDWT-DCT-SVD with PSA optimization is compared with various existing BW approaches in terms of various quality metrics like peak signal to noise ratio (PSNR), structural similarity (SSIM) index, root mean square error (RMSE) and normalized correlation coefficient (NCC).

Image Watermarking Using All Phase Discrete Cosine Biorthogonal Transform in Selected Pixel Blocks

In the past decade, a transform called all phase discrete cosine biorthogonal transform (APDCBT) appeared in the field of digital image processing. It is mainly used to solve the negativity found in discrete cosine transform (DCT), especially in a low bit rate. In this paper, the APDCBT is employed for watermark insertion based on selected regions of an image. The insertion is depending on the homogeneity of each part of the image. To determine the extent of homogeneity, there are two criteria: Mean and standard deviation are applied for the intensity of the image. Medium frequency bands of APDCBT in image pixel blocks are used to hold the embedded watermark. Then, the transform is inversed to obtain the resultant watermarked image. The robustness of APDCBT against watermark removal attacks is tested and the experimental results showed the superiority of the APDCBT over traditional DCT in the watermark embedding system. More specifically, when the LSB reset attack applied. For instance, when the contrast adjustment attack applied, the average of normalized cross-correlation (NCC) values of extracted watermark images with the original watermark, it was 0.992 for the proposed method. This is a promised result, if it is compared with the NCC of the DCT method, which was 0.423. The proposed method can be used for copyright protection purpose.

Performance comparison of recent optimization algorithm Jaya with particle swarm optimization for digital image watermarking in complex wavelet domain

Nowadays copyright protection is mandatory in the field of image processing to removes the illegitimate utilization and imitation of digital images. The digital image watermarking is one of the most reliable methods for protecting the illegal validation of data. In this paper, singular value decomposition based digital image watermarking scheme is proposed in complex wavelet transform (CWT) domain using intelligence algorithms like particle swarm optimization (PSO) and recently proposed Jaya algorithm. The watermark image is embedded into high frequency CWT subband of cover image. At the time of watermark embedding and extraction, optimization algorithms Jaya and PSO are applied to improve the robustness and imperceptibility by assessing the fitness function. The perceptual quality of watermarked image and robustness of extracted watermark image are verified under the filtering, rotation, scaling, Gaussian noise and JPEG compression attacks. From the comparative analysis it is proved that Jaya algorithm is better as compared to PSO algorithm under most types of attacks with higher magnitudes whereas identical under the lower magnitude of applied attacks. Moreover, using variety of cover images, it is found that, the elapse time and value of fitness function given by Jaya algorithm are also better as compared to PSO.

Robust Scene-Based Digital Video Watermarking Scheme Using Level-3 DWT: Approach, Evaluation, and Experimentation

This paper presents a robust digital video-watermarking system for copyright and copy protection. The proposed method applies the combination of discrete wavelet transform (DWT) and scene-change-detector. For better understanding, this approach can be presented in the form of four stages. The first stage is finding the frame where the watermark is to be inserted. The analysis of watermarking using the level-3 decomposition of LL subband with DWT is described in the second stage. Transparency and the robustness have been analyzed under fifteen different attacks in the third stage. Improvement in the robustness and transparency, as compare to watermarking using different levels of LL subband is calculated in terms of the normalized correlation and the structural similarity index in the fourth stage. The experimental result reveal that the proposed method yields the extracted watermark image and watermarked video of good quality and can sustain different image processing, JPEG compression and geometrical attacks. Empirical results prove the improvement in the performance as the decomposition level increases from level-1 to level-3. Comparative analysis with the existing schemes proves the improved robustness, better imperceptibility and the reduced computational time of the proposed scheme.

A new approach for colored watermarking image into gray scale image using wavelet fusion

With the quick growth of technologies and great spread of the Internet, many challenges face data hiding. Nevertheless, significant data may be protected by burring it in an image as a watermark. This paper shows an efficient data hiding watermarking approach for color image by using singular value decomposition (SVD), multi-level discrete wavelet transform (DWT) and wavelet fusion. The main idea in this work is to separate the color image into its basic components (three channels); red, green, and blue. Then, fuse every channel with an image which is gray scale and integrate the three fused images into one gray scale fused image. Finally, the fused image is burred into a cover gray scale image to produce the watermarked image by using DWT and SVD. The proposed approach evaluation is done by using several images and different hacking on the transmitted image. The experimental results show that the marked images which are generated by the proposed approach are tolerant to versatile attacks such as Gaussian, blur, wrap, and cropping. Above all, the extracted watermark images are recognized even when the watermarked images suffered from attacks.

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.

Robust watermarking algorithm for digital images using discrete wavelet and probabilistic neural network

Digital watermarking, which has been proven effective for protecting digital data, has recently gained considerable research interest. This study aims to develop an enhanced technique for producing watermarked images with high invisibility. During extraction, watermarks can be successfully extracted without the need for the original image. We have developed discrete wavelet transform with a Haar filter to embed a binary watermark image in selected coefficient blocks. A probabilistic neural network is used to extract the watermark image. To evaluate the efficiency of the algorithm and the quality of the extracted watermark images, we used widely known image quality function measurements, such as peak signal-to-noise ratio (PSNR) and normalized cross correlation (NCC). Results indicate the excellent invisibility of the extracted watermark image (PSNR=68.27dB), as well as exceptional watermark extraction (NCC=0.9779). Experimental results reveal that the proposed watermarking algorithm yields watermarked images with superior imperceptibility and robustness to common attacks, such as JPEG compression, rotation, Gaussian noise, cropping, and median filter.

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.

A semi-blind digital watermarking scheme based on singular value decomposition

This paper presents a robust watermarking approach for hiding grayscale watermarks into digital images. Plugging the codebook concept into the singular value decomposition (SVD), the proposed method embeds the singular values (SVs) of the original image into the watermark one to attain the lossless objective. The experimental results show that the proposed scheme guarantees the extracted watermark on an average and the worst PSNR values of 24.91 and 19.96 dB, respectively. In addition to the guarantee of the quality of extracted watermark image, the security of the referenced watermark is further strengthened by applying chaos permutation on it in advance. The proposed scheme leads to satisfactory robustness to various attacks and is compared to other well-known grayscale watermarking methods to reveal its efficiency for practical applications.