A Highly Secured Digital Watermarking Algorithm for Binary Watermark Using Lifting Wavelet Transform and Singular Value Decomposition

Rapid development of the digital technology and internet has made copyright protection and ownership verification of digital audio data hot research topics that have attracted a lot of interest from different parties. Since the traditional audio protection algorithms cannot solve all the problems of audio copyright protection and digital right management (DRM) due to the unique audio data features and algorithm limitations, this thesis is proposed to address the issue of audio copyright protection using watermarking techniques. Firstly, a new perception-based watermarking scheme for MPEG-4 scalable to lossless (SLS) audio is proposed. Under the control of the psychoacoustic model, the significant part of integer modified discrete cosine transform (IntMDCT) coefficients are adaptively modified during MPEG-4 SLS audio compression taking robustness, imperceptibility and security into consideration. The chaotic watermark generated by chaos is then embedded to ensure security. Moreover, the adaptive spread spectrum (SS) method is exploited to further optimize the tradeoff between robustness and transparency of this scheme. Secondly, a blind and robust audio watermarking scheme based on singular value decomposition (SVD) – followed by discrete cosine transform (DCT) with the synchronization code technique is proposed. A binary watermark is embedded into the high frequency band of the SVD-DCT block. Chaotic sequence is adopted as the synchronization code and inserted into the host signal. Thirdly, a new and robust audio watermarking scheme based on lifting wavelet transform (LWT) and SVD is proposed. Specifically, the watermark data is efficiently inserted in the low coefficient of the frequency subband of LWT audio taking advantage of both SVD and quantization index modulation (QIM). Furthermore, the synchronization code technique is also integrated in the hybrid LWT-SVD audio watermarking method. Finally, a particle swarm optimization (PSO) and SVD based audio watermarking scheme is proposed. The watermark is embedded by modifying singular values (SVs) of the host audio signal with the SS method. The designed optimization technique employs PSO to search for the optimal watermark strength by continuously adjusting the fitness values so that the conflicting requirements of robustness and imperceptibility of the watermark are satisfied optimally. Moreover, the proposed scheme has the flexibility to include or remove various watermarking attacks during training for optimization. The experimental results validate the practicality of the proposed methods and show that the proposed algorithms are very robust to typical signal manipulations. Furthermore, the results of comparison with other similar state-of-the-art audio watermarking techniques indicate that the proposed algorithms are more robust against most common signal processing attacks while preserving good imperceptibility.

This paper proposes a novel scheme combining Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) for image watermarking. The watermarking image is separated by two parts randomly, then they are embedded into the sub-bands obtained from the original image in DWT domain by modifying the singular value. SVD is applied twice in this scheme.The use of the threshold of Just Noticeable Distortion (JND) based on human visual model determines the embedding strength and position of the watermark, the digital adaptive watermarking algorithm in a combinational domain is realized. The experimental results show that the proposed scheme has a good invisibility and performance of robustness for common attacks, simultaneously enhances the embedding capacity and security.

A significant data protection technique for a number of problems, the most prominent being identity authentication and copyright protection, is digital image watermarking. The rapid digital transformation of the world has given rise to a variety of vision modification techniques, which have significant consequences for picture data security. As a result, maintaining the validity and integrity of digital images is crucial, which is why researchers are focusing on creating effective watermarking techniques. This study proposes an optimized robust watermarking technique based on lifting wavelet transform (LWT) with singular value decomposition (SVD) using the particle swarm optimization (PSO) algorithm for achieving multiple scaling factors (MSF). To increase security and durability, cover images are exposed to numerous attacks. The evaluation criteria, which encompass normalized cross-correlation (NCC) and peak signal-to-noise ratio (PSNR), were used to compare our outcomes with those of leading watermarking methods. The comparison reveals that our proposed strategy surpasses existing methods in terms of both robustness and imperceptibility. The results suggest that this technique is suitable for tamper detection in various domains, including cryptography, medical imaging and multimedia transmission.

The users of networks are increasing rapidly due to increase in growth of internet. There is always a concern among owners of the digital products about illegal copying of their products. Important issues in multimedia applications and services today are Security and copyright protection. Digital watermarking is a technology used for copyright protection of images videos etc. that is stored on internet. Here own right information data called watermark is embedded into the digital media without affecting the perceptual quality of video. In case if any dispute arises, it is possible to detect or extract the watermark data from the media and it can be used as an ownership proof. Digital video watermarking scheme is based on Discrete Wavelet Transform and Singular Value Decomposition. Design of this scheme using Matlab is proposed. Embedded watermark is robust against various attacks that can be carried out on the watermarked video.

In this paper, a new optimal watermarking scheme based on singular value decomposition (SVD) and lifting wavelet transform (LWT) using multi-objective genetic algorithm optimization (MOGAO) is presented. The singular values of the watermark is embedded in a detail subband of host image. To achieve the highest possible robustness without losing watermark transparency, multiple scaling factors (MSF) are used instead of single scaling factor (SSF). Determining the optimal values of the MSF's is a difficult problem. However, to find this values a multi-objective genetic algorithm optimization is used. Experimental results show a much improved performance in term of transparency and robustness of the proposed method compared to others methods.

In this paper, a robust image watermarking technique has been proposed in lifting wavelet transform (LWT) domain. Neural network is incorporated in the watermark extraction process to achieve improved robustness against different attacks. The integration of neural network with LWT makes the system robust to various attacks maintaining an adequate level of imperceptibility. The 3-level LWT coefficients are randomized and arranged in 2×2 non-overlapping blocks. Each block is modified according to a binary watermark bit. Randomization of coefficients and blocks has been done to enhance the security of the system. The binary watermark bit is also encrypted using another key. The scheme provides an average imperceptibility of 43.88 dB for a watermark capacity of 512 bits. The robustness has been observed against all the intentional and non-intentional attacks. The technique provides satisfactory robustness against different attacks such as noising attacks, de-noising attacks, lossy compression attacks, image processing attacks and some geometric attacks. The algorithm has been tested on a large image database containing different class of images.

In this proposed work, a dual image watermarking algorithm is used to protect the data against copyright violations. In this work, the DICOM image is used as a host image. Two watermark images used are the MNNIT logo and the personal data of the patient. This method utilizes the advantages of Schur decomposition, lifting wavelet transform (LWT), discrete cosine transform (DCT) and singular value decomposition (SVD). The scaling factor is a vital parameter of watermarking technique. The firefly optimization technique is used to get the optimized scaling factor. The Speeded-up robust features (SURF) are used for watermarking authentication. To evaluate the performance of the proposed algorithm, peak signal-to-noise ratio (PSNR), normalized correlation coefficient (NCC), and structural similarity index measurement (SSIM) are used. The proposed method is tested against various attacks such as Salt and Pepper noise, Gaussian noise, Gaussian low pass filter, Average filter, Median filter, Histogram equalization, Sharpening, Rotation and Region of interest filtering. The proposed algorithm shows a high level of robustness and imperceptibility. It is found that the features of the input host image and the watermarked image are matching correctly on applying the SURF technique.

Digital watermarking is an emerging solution for securing multimedia products from illegal or unauthorized manipulation. Robustness and visual imperceptibility are two characteristics of watermarking, which can be achieved by utilizing various transform techniques. Our proposed robust watermarking technique used a hybrid transform composed of three transform techniques: nonsubsampled contourlet transform (NSCT), all phase discrete cosine biorthogonal transform (APDCBT), and singular value decomposition (SVD). NSCT has outstanding shift-invariant, and directional properties; its low-frequency band of an image contains a large amount of visual information. Besides, APDCBT can attenuate the high-frequency components, and its direct current (DC) components have more visual details of an image. For gathering these DC components, we applied APDCBT on the low-frequency band of NSCT of a cover image after 8 × 8 block portioning. Then the binary watermark is inserted into perceptually significant DC components using SVD. The feasibility of the proposed technique is justified using computer simulation as well as this scheme is passed through imperceptibility and robustness test. Finally, a comparative analysis demonstrates that our proposed method achieves satisfactory improvements over the existing two watermarking techniques.

The technology development has made the modification of digital content easier. The need of authenticating digital content is increasing. Image authentication can be done by embedding a mark in the image using digital fragile watermarking. In this paper we propose a new approach for image authentication based on Faber Schauder Discrete Wavelet Transform (FSDWT) and Singular Value Decomposition (SVD). The watermark used to authenticate the image is extracted from the image dominant blocks using SVD and FSDWT. This watermark is embedded in the LSB plan of image. This one is characterized by its contours and its around textures which contain an important concentration of dominant coefficients that are used to select the dominant blocks. Any image modification will result in an important change in the dominant blocks. Hence, if the image is altered, the singular values of the dominant blocks will be dramatically changed, then we confirm that the image is not authentic.

Watermarking is one of the widely used applications to provide security for the content shared over internet. Internet is a place where the data is not of assured security to the fullest. DTCWT is widely used in all image processing applications over a decade. A novel imperceptible video watermarking scheme is proposed. This method is implemented with the use of Dual Tree Complex Wavelet Transform (DTCWT) and Singular value decomposition (SVD) which helps in proof of ownership. In this method Singular Value Decomposition is applied to the Dual Tree Complex Wavelet Transform (DTCWT) coefficients of both watermark and original image and the singular Eigen values are interchanged. Because of advantages, Shift invariance and Directionality we prefer DTCWT. As SVD decomposes the matrix into 3 matrices U, S, V, we need U, V at the time of extraction. So we use U, V as watermark in audio. Watermark extracted from the audio gives the U, V matrices which makes this method blind watermarking. In order to prove the robustness of the method the results are compared with similar algorithms proposed in this paper but with DWT.

With increasing development of information technology, electronic publishing is becoming more popular, so need for copyright protection has been increased. Digital watermarking is used to protect digital data from being altered. This paper presents an algorithm to embed fractal images in wavelet domain using LWT (Lifting Wavelet Transform). Fractal image is generated from Quadtree decomposition and converted into binary image. This binary image is used as watermark. Cover image is converted into RGB components and binary watermark is inserted into mid frequency bands of cover image to protect information from attackers. Watermark is implanted in the blue component of RGB image. The PSNR, SSIM, and NC values obtained in this research show that the method is imperceptible and robust against signal distortions such as contrast enhancement, gamma correction, image sharpening, Gaussian filter, etc.

Watermarking is crucial for protecting medical images, guaranteeing data integrity and authenticity in telemedicine, especially for rural healthcare facilities with limited computational power. This paper introduces a lightweight watermarking scheme that performs a comparative study of Lifting Wavelet Transform (LWT) versus Discrete Wavelet Transform (DWT), both combined with Discrete Cosine Transform (DCT), to achieve optimal imperceptibility, robustness, and computational efficiency. The comparison of LWT and DWT is essential because LWT has lower computational complexity and memory usage, hence more appropriate for resource-limited environments than DWT, and without the use of Singular Value Decomposition (SVD) to further reduce processing requirements and improve compatibility with low-power devices. The suggested approach adopts adaptive embedding against texture complexity, secure synchronization patterns with m-sequences and Barker codes, and geometric correction utilizing ORB for guaranteed watermark extraction under attacks from JPEG compression, Gaussian noise attack, rotation attack, median filter attack, and Gaussian blur. A new error correction code interleaved with majority voting is employed to increase the watermark’s strength. Tested at various embedding strengths, the scheme attains Peak Signal to Noise Ratio (PSNR) values over 40 dB and Structural Similarity Index (SSIM) values above 0.95, signifying extremely little visual degradation. Low Bit Error Rates (BER) and high Normalized Correlation (NC) in various attack scenarios validate its success. This computational-friendly solution is designed to arm remote healthcare organizations with limited computer ability to reliably authenticate and attest to medical images, meeting severe telemedicine demands.

Digital Image Watermarking provides a successful method for content authentication and copyright protection. Thus, it has significant scope in today's era due to the rapid growth of internet users. The watermark should be robust and reliable in addition to being imperceptible to the human eye. In this paper, a hybrid singular value decomposition (SVD) and discrete wavelet transform (DWT) based watermarking scheme is presented. The SVD used in this scheme is a variant of the traditional SVD and is called shuffled SVD (SSVD). The cover image is decomposed into four sub-bands (LL, HL, LH, HH) using DWT. The LL subband is further divided into blocks of appropriate size. The principle components of the watermark image obtained after applying SSVD are embedded in various blocks of the LL sub-band. The proposed scheme shows significant robustness in addition to being false positive free.

Watermarking is a useful technique for copyright management. It is widely used in various types of digital content management application of grayscale and colour images. But as of now, there has been no method to watermark for a grayscale image using a colour image. In this paper, a unique watermarking for the grayscale image scheme in the transform domain has been proposed. The presented technique is suitable for the digital rights and security management of the diagnostic medical images in the online database. The proposed watermarking method is composed of Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD). Additionally, we have used the Firefly Algorithm (FA) to compute appropriate scaling factor to achieve higher perceptibility and robustness. Performance metrics such as PSNR, SSIM, and NCC are used to evaluate the technique. Experimental analysis shows that the proposed technique is 40-45% improved over the existing methods and almost 50% watermark is recoverable under different image processing attacks proving robustness of the technique.

This paper developed new and efficient image watermarking scheme for copyright protection based on Lifting wavelet transform (LWT) and Bi- dimensional Empirical Mode Decomposition (BEMD). A LWT has been selected because it is fast, less computational cost and maintains the integrity of the recovered watermark. The BEMD transform can separate the image from the most robust to the least sensitive or fragile frequency bands. This advantage is utilised in this study for the purpose of embedding the watermark in the robust part of BEMD, i.e. the residue (r). In addition, the embedding process has been performed in the low sub-band of LWT decomposed image as the low sub-band is more robust to image processing such as JPEG compression. The robust watermark which is grey scale image is decomposed using DWT to enhance the security and select only high sub-band as it has less impact on the quality of the watermarked image. As a result, the original image’s visual quality can be preserved and the concealed watermark could be successfully retrieved even if the watermarked images have undergone severe attacks like JPEG, rotation, Gamma correction, filtering, additive noise, translation, shearing, and scaling. Furthermore, the improved scheme offers greater robustness against many image processing operations, in comparison to the current schemes about copyright protection.