Query: watermarking

title: A block based RDWT SVD image watermarking method using human visual system characteristics
abstract: With the rapid growth of internet technology, image watermarking method has become a popular copyright protection method for digital images. In this paper, we propose a watermarking method based on $4\times 4$ 4 x 4 image blocks using redundant wavelet transform with singular value decomposition considering human visual system (HVS) characteristics expressed by entropy values. The blocks which have the lower HVS entropies are selected for embedding the watermark. The watermark is embedded by examining $U_{2,1} U 2 1 and $U_{3,1} U 3 1 components of the orthogonal matrix obtained from singular value decomposition of the redundant wavelet transformed image block where an optimal threshold value based on the trade off between robustness and imperceptibility is used. In order to provide additional security, a binary watermark is scrambled by Arnold transform before the watermark is embedded into the host image. The proposed scheme is tested under various image processing, compression and geometrical attacks. The test results are compared to other watermarking schemes that use SVD techniques. The experimental results demonstrate that our method can achieve higher imperceptibility and robustness under different types of attacks compared to existing schemes. Our method provides high robustness especially under image processing attacks, JPEG2000 and JPEG XR attacks. It has been observed that the proposed method achieves better performance over the recent existing watermarking schemes.

title: SPIHT based multiple image watermarking in NSCT domain
abstract: Image watermarking in wavelet domain is a challenging problem as it includes a proper selection of wavelet transforms as well as sub bands for accurate embedding and recovery of watermarks. However, selection of a suitable wavelet transform for multiple image watermarking is an area of great interest. Therefore, in this work, a multiple watermarking technique using combination of redundant discrete wavelet transforms (RDWT) non subsampled contourlet transform (NSCT) set partitioning in hierarchical tree (SPIHT) and singular value decomposition (SVD) is proposed. The proposed scheme is aimed to achieve high capacity, robustness, and imperceptibility. The security aspect of the proposed method is enhanced by using Arnold transform. Since RDWT and NSCT are both shift invariant in nature, therefore they are suitable for multiple image watermarking. Furthermore, the proposed method provides flexibility in selection of appropriate sub bands for watermark embedding and recovery. Experimental results and analysis reveals that the proposed technique gives maximum PSNR, NC, and SSIM value up to 40.97 dB, 1, and 0.9994, respectively. Furthermore, the performance estimation of our technique is found superior to previously reported techniques under consideration.

title: Pattern complexity based JND estimation for quantization watermarking
abstract: The perceptual just noticeable distortion (JND) which plays an important role in perceptual image watermarking and can refers to the optimal tradeoff between imperceptibility and robustness. Major challenges of the perceptual quantization watermarking approach are two fold: (1) Most DCT based JND models cannot accurately estimate the contrast masking effect due to the complicated interaction among visual contents. Research on cognitive science shows that the HVS is adaptive to extract the visual pattern for image understanding, and we can formulate the pattern complexity as another factor to determine the total watermarking strength. (2) Moreover, the calculated JND values will change as watermark embedding can affect the pixels of the image, i.e. the operation in cross domain reduce the watermarking robustness. Therefore, in this regard, the maximum directional energy is calculated by three AC DCT coefficients, which can measure the different direction energy and keep the pattern complexity measurement insensitive to the changes caused by watermarking procedure. The luminance contrast is also calculated in the DCT domain. So a pattern complexity based perceptual JND estimation model is designed by takeing DCT based pattern complexity and luminance contrast into account. Furthermore, a new logarithmic quantization watermarking scheme is presented based on the proposed model to verify the feasibility and effectiveness of our proposed JND model. Experimental results show that the new built JND model can effectively enhance the robustness of the quantization watermarking scheme.

title: An efficient watermarking technique for tamper detection and localization of medical images
abstract: With the exponential rise of multimedia technology and networked infrastructure, electronic healthcare is coming up a big way. One of the most important challenges in an electronic healthcare setup is the authentication of medical images, received by an expert at a far off location from the sender. With an aim to address the critical authentication issue, this paper presents a fragile watermarking technique capable of tamper detection and localization in medical/general images. We divide the cover image into 4 x 4 non overlapping pixel blocks; with each block further sub divided into two 4 x 2 blocks, called as Upper Half Block (UHB) and Lower Half Block (LHB) The information embedded in LHB facilitates tamper detection while as that embedded in UHB facilities tamper localization. The experimental results show that, in addition to tamper detection and localization capability, the proposed technique has lesser computational complexity when compared to other state of art techniques. Further, the proposed scheme results in average PSNR of 51.26 dB for a payload of one bit per pixel (1bpp) indicating that the watermarked images obtained are of high visual quality.

title: KeySplitWatermark: Zero Watermarking Algorithm for Software Protection Against Cyber Attacks
abstract: Cyber attacks are evolving at a disturbing rate. Data breaches, ransomware attacks, crypto jacking, malware and phishing attacks are now rampant. In this era of cyber warfare, the software industry is also growing with an increasing number of software being used in all domains of life. This evolution has added to the problems of software vendors and users where they have to prevent a wide range of attacks. Existing watermark detection solutions have a low detection rate in the software. In order to address this issue, this paper proposes a novel blind Zero code based Watermark detection approach named KeySplitWatermark, for the protection of software against cyber attacks. The algorithm adds watermark logically into the code utilizing the inherent properties of code and gives a robust solution. The embedding algorithm uses keywords to make segments of the code to produce a key dependent on the watermark. The extraction algorithms use this key to remove watermark and detect tampering. When tampering increases to a certain user defined threshold, the original software code is restored making it resilient against attacks. KeySplitWatermark is evaluated on tampering attacks on three unique samples with two distinct watermarks. The outcomes show that the proposed approach reports promising results against cyber attacks that are powerful and viable. We compared the performance of our proposal with state of the art works using two different software codes. Our results depict that KeySplitWatermark correctly detects watermarks, resulting in up to 15.95 and 17.43 percent reduction in execution time on given code samples with no increase in program size and independent of watermark size.

title: ReDMark: Framework for residual diffusion watermarking based on deep networks
abstract: Due to the rapid growth of machine learning tools and specifically deep networks in various computer vision and image processing areas, applications of Convolutional Neural Networks for watermarking have recently emerged. In this paper, we propose a deep end to end diffusion watermarking framework (ReDMark) which can learn a new watermarking algorithm in any desired transform space. The framework is composed of two Fully Convolutional Neural Networks with residual structure which handle embedding and extraction operations in real time. The whole deep network is trained end to end to conduct a blind secure watermarking. The proposed framework simulates various attacks as a differentiable network layer to facilitate end to end training. The watermark data is diffused in a relatively wide area of the image to enhance security and robustness of the algorithm. Comparative results versus recent state of the art researches highlight the superiority of the proposed framework in terms of imperceptibility, robustness and speed. The source codes of the proposed framework are publicly available at Github 1

title: An improved DWT SVD domain watermarking for medical information security
abstract: Exchange of patient record over network required a technique to guarantee security and privacy for tele health services. This paper presents an improved watermarking technique capable of providing protection of patient data by embedding multi watermarks in medical cover image using DWT SVD domain. Prior to embedding, Hamming code is applied to text watermark in order to reduce channel noise distortion for the sensitive data. After embedding, the watermarked medical image is encrypted then compressed. Out of two encryption method and three compression scheme tested, combination of Chaotic LZW shows the best performance. However, HyperChaotic LZW combination is more robust against Gaussian, JPEG compression, speckle noise and histogram equalization attacks. We illustrate the good results in terms of objective and subjective evaluation, and verify its robustness for various attacks while maintaining imperceptibility, security and compression ratio. Experimental results demonstrate that the suggested technique archives high robustness against attacks in comparison to the other scheme for medical images.

title: An improved watermarking algorithm for color image using Schur decomposition
abstract: In order to protect the color image copyright protection of the multimedia big data, it is necessary to design a color image watermarking algorithm. To achieve this purpose, an improved color image watermarking algorithm based on Schur decomposition is proposed in this paper. First, the watermark information is, respectively, embedded into the upper triangular matrix and the unitary matrix of Schur decomposition by two different methods, and two temporary watermarked image blocks are obtained. Then, the proposed improved method is used to select the final watermarked image block from these temporary watermarked image blocks. The highlight of the proposed method is that the final watermarked block has less visual distortion. Meanwhile, the embedded flag is created and uploaded to the cloud service provider with the watermarked image. When extracting watermark, the original host image or the watermark image is not needed. Experimental results show that the proposed watermarking algorithm has better performance; in particular, the watermark invisibility has been obviously improved than other methods considered in this paper.

title: Color image watermarking based on orientation diversity and color complexity
abstract: can reliably measure the perceptual strength in image watermarking, but, it remains a challenge to computationally model the process of embedding watermark without prior knowledge of the image contents. This paper proposed a novel color image watermarking scheme in discrete cosine transform (DCT) domain based on JND, which takes both orientation diversity and color complexity features into account. Firstly, two indicator was introduced which take into account the differences in the texture types and orientation diversity of the Human Visual System (HVS) in the proposed JND contrast masking (CM) processing. In addition, a novel color complexity weight from Cb channel is used to guarantee the scheme robustness. Then, a novel JND model combined with the proposed contrast masking and color complexity is applied into quantization watermarking scheme. Compared with the state of the art methods for color image watermarking, experimental results using publicly available images show that our proposed scheme is reliable and effective.

title: Fractional Charlier moments for image reconstruction and image watermarking
abstract: In this paper, we propose a new set of discrete orthogonal polynomials called fractional Charlier polynomials (FrCPs) This new set will be used as a basic function to define the fractional discrete orthogonal Charlier moments (FrCMs) The proposed FrCPs are derived algebraically using the spectral decomposition of Charlier polynomials (CPs) then the Lagrange interpolation formula is used to derive the spectral projectors. Then, each spectral projector matrix is decomposed by the singular value decomposition (SVD) technique in order to build a basic set of orthonormal eigenvectors which help to develop FrCPs. FrCMs are deduced in matrix form from the proposed FrCPs and are applied for image reconstruction and watermarking. The experimental results show the capacity of the FrCMs proposed for image reconstruction and image watermarking against different attacks such as noise and geometric distortions.