Robust Watermarking Research Articles

Screen-Shooting Resilient Watermarking Scheme via Learned Invariant Keypoints and QT.

This paper proposes a screen-shooting resilient watermarking scheme via learned invariant keypoints and QT; that is, if the watermarked image is displayed on the screen and captured by a camera, the watermark can be still extracted from the photo. A screen-shooting resilient watermarking algorithm should meet the following two basic requirements: robust keypoints and a robust watermark algorithm. In our case, we embedded watermarks by combining the feature region filtering model to SuperPoint (FRFS) neural networks, quaternion discrete Fourier transform (QDFT), and tensor decomposition (TD). First we applied FRFS to locate the embedding feature regions which are decided by the keypoints that survive screen-shooting. Second, we structured watermark embedding regions centered at keypoints. Third, the watermarks were embedded by the QDFT and TD (QT) algorithm, which is robust for capturing process attacks. In a partial shooting scenario, the watermark is repeatedly embedded into different regions in an image to enhance robustness. Finally, we extracted the watermarks from at least one region at the extraction stage. The experimental results showed that the proposed scheme is very robust for camera shooting (including partial shooting) different shooting scenarios, and special attacks. Moreover, the efficient mechanism of screen-shooting resilient watermarking could have propietary protection and leak tracing applications.

Robust watermarking of databases in order-preserving encrypted domain

Robust watermarking of databases in order-preserving encrypted domain

Blind robust image watermarking based on adaptive embedding strength and distribution of quantified coefficients

The image watermarking technique is a reliable method for protecting digital image rights. The most widely used digital imaging format is the JPEG (joint photographic expert’s group). This paper proposes a novel reversible robust watermarking scheme based on the JPEG image. In JPEG image, quantified Discrete Cosine Transform (DCT) coefficients with varying frequency provide varied capacities and embedding deformities. To minimize total distortion for the watermarked image, we adaptively select embedding strengths and coefficients from effective frequency selection that produce less embedding distortions. Then, by weighting the difference between the quantified DCT coefficient and the DCT coefficient on the block, an advanced block selection strategy is used to the corresponding distortion, which are produced from the whole quantified alternating current (AC) shift capacity and half of the insertion capacity. The experimental results show that the proposed method can maintain good visual quality while requiring little bitstream expansion and is robust to geometrical and image processing attacks.

Dual secure robust watermarking scheme based on hybrid optimization algorithm for image security

Dual secure robust watermarking scheme based on hybrid optimization algorithm for image security

Secured telemedicine of medical imaging based on dual robust watermarking

Secured telemedicine of medical imaging based on dual robust watermarking

Towards High-Resolution Copy-Evident Ceramic Tiles: A Deep Learning Framework for Halftoning and Watermarking

Ceramic art is essential in interior design and decoration, and making exquisite ceramic tiles imposes strict requirements for inkjet printing technology. High-resolution ceramic tiles are often produced through inkjet printing, in which the input images are converted into a halftone format. However, traditional binary halftoning techniques cannot produce high-resolution images for the ensuing printing process. Given that the processes of inkjet printing and high-temperature firing of ceramic tiles are a highly complex nonlinear system, and existing halftoning methods pose intractable problems, including inconsistent textures and color deviations. Based on a modified U-Net model and a modified error diffusion algorithm, we propose a multilevel halftoning method, which is capable of converting color-separation images of ceramic tiles into high-resolution halftone images. To deter copyright infringement, we further apply an ad hoc invisible watermarking method for halftone images. In this paper, we propose a four-stage framework: (1) A self-built dataset is used to solve non-convergence and overfitting problems caused by the unbalanced samples and non-uniqueness of halftone images. (2) A modified U-Net model is trained on the self-built dataset and applied to the ceramic-tile images. (3) An improved error diffusion algorithm is used to calibrate and convert the predicted continuous-tone transition images into multilevel halftone images for inkjet printing. (4) A invisible and robust watermark is embedding algorithm towards halftone images is proposed for copyright protection. Experimental results show that our methodology is effective for performing the color-to-halftone transformation and identifying the copyright.

GIFMarking: The robust watermarking for animated GIF based deep learning

Animated GIF has become a key communication tool in contemporary social platforms thanks to highly compatible with affective performance, and it is gradually adopted in commercial applications. Therefore, the copyright protection of the animated GIF requires more attention. Digital watermarking is an effective method to embed invisible data into a digital medium that can identify the creator or authorized users. However, few works have been devoted to robust watermarking for the animated GIF. One of the main challenges is that the animated image also contains time frame dimension information compare with still images. This paper proposes a robust blind watermarking framework based 3D convolutional neural networks for the animated GIF image, which achieves watermark image embedding and extraction for the animated GIF. Also, noise simulation is developed in frame-level to ensure robustness for the attack of the temporal dimension in this framework. Furthermore, the invisibility of the watermarked animated image is optimized by adversarial learning. Experimental results provide the effectiveness of the proposed framework and show advantages over existing works.

Improving DFT-Based Image Watermarking Using Particle Swarm Optimization Algorithm

Robust digital image watermarking is an information security technique that has been widely used to solve several issues related mainly with copyright protection as well as ownership authentication. In general terms, robust watermarking conceals a small signal called a “watermark” in a host image in a form imperceptible to human vision. The efficiency of conventional robust watermarking based on frequency domain depend directly on the results of performance in terms of robustness and imperceptibility. According to the application scenario and the image dataset, it is common practice to adjust the key parameters used by robust watermarking methods in an experimental form; however, this manual adjustment may involve exhaustive tasks and at the same time be a drawback in practical scenarios. In recent years, several optimization techniques have been adopted by robust watermarking to allowing adjusting in an automatic form its key operation parameters, improving thus its performance. In this context, this paper proposes an improved robust watermarking algorithm in discrete Fourier transform via spread spectrum, optimizing the key operation parameters, particularly the amounts of bands and coefficients of frequency as well as the watermark strength factor using particle swarm optimization in conjunction with visual information fidelity and bit correct rate criteria. Experimental results obtained in this research show improved robustness against common signal processing and geometric distortions, preserving a high visual quality in color images. Performance comparison with conventional discrete Fourier transform proposal is provided, as well as with the current state-of-the-art of particle swarm optimization applied to image watermarking.

A Hybrid robust watermarking system based on discrete cosine transform, discrete wavelet transform, and singular value decomposition

Digital data sharing is increased day by day due to the rapid access of the Internet by mass people. Multimedia, for example text, image, video, and audio can be easily accessed by unauthorized users. To ensure multimedia security, researchers are focusing on digital image watermarking. A robust watermarking system must satisfy the basic design requirements like imperceptibility, robustness, security, and payload capacity. Watermarking can be embedded into a host image through different transform operations, such as discrete cosine transform (DCT), discrete wavelet transform (DWT), and singular value decomposition (SVD). However, a single transformation does not ensure all the design requirements simultaneously. To fill this gap, a hybrid blind digital image watermarking with a combination of DCT, DWT, and SVD is proposed in this paper. At first, the Arnold map is used to encrypt the watermark image. Then DCT is applied to it and to the host image followed by DWT before SVD. After that, the watermarked image is generated by embedding the watermark image into the host image. The performance is evaluated under various attacks and experimental results show that our algorithm ensures improved robustness while preserving high imperceptibility and enhanced security than the state-of-the-art methods.

Digital Hologram Watermarking Based on Multiple Deep Neural Networks Training Reconstruction and Attack

This paper proposes a method to embed and extract a watermark on a digital hologram using a deep neural network. The entire algorithm for watermarking digital holograms consists of three sub-networks. For the robustness of watermarking, an attack simulation is inserted inside the deep neural network. By including attack simulation and holographic reconstruction in the network, the deep neural network for watermarking can simultaneously train invisibility and robustness. We propose a network training method using hologram and reconstruction. After training the proposed network, we analyze the robustness of each attack and perform re-training according to this result to propose a method to improve the robustness. We quantitatively evaluate the results of robustness against various attacks and show the reliability of the proposed technique.

A Reframed Watermark Extraction Approach Using the ABC Algorithm

The fast development and the rapid spread of information technology have raised the issue of digital-image copyright protection, which was mostly addressed through robust watermarking. To ensure the survival of the watermark after attacks, most works have been making use of an additional step at the embedding phase, and by so making the scheme unsuitable for real-time implementation. However, to be effective and secure, it is recommended to combine the watermarking algorithm and the capture sensor in one device. In this paper, we brought the extra stage to the detection side. We firstly studied the effect of some signal processing operations on a watermarked image, then we proposed a general model for watermark extraction whose parameters were determined using the artificial bee colony. The efficacy of the proposed method was validated by comparing its robustness with two state-of-art schemes focusing on the watermark extraction.

Robust and Secure Watermarking for Propagation of Digital Multimedia by Paillier Homomorphic Cryptosystem With Arnold Transformation

Sharing of digital media over internet is becoming easier due to content authentication and security provided by digital watermarking. It also locates application in other fields like copyright protection, tele-medicine, military, tamper detection, and many more. This paper represents the robust watermarking approach using Paillier homomorphic cryptosystem with Arnold transformation. In this, the watermarking system is primarily prepared at an encrypted DWT-DCT domain. Cryptosystem is exploited at this time to encrypt the original media. For more security of multimedia content, the watermark image is scrambled through Arnold scrambling technique. The embedding process is done here to produce the encrypted watermark image followed by the encryption process. At recovery phase, decryption of encrypted watermark image to get the original and watermark image is done. The experimental result has shown that watermarking method is more robust and offers the security of digital media.

Geometrically Invariant NSCT–GPCET-Based Image Watermarking with Accurate Moment Calculation

Generic polar complex exponential transform (GPCET), as continuous orthogonal moment, has the advantages of computational simplicity, numerical stability, and resistance to geometric transforms, which make it suitable for watermarking. However, errors in kernel function discretization can degrade these advantages. To maximize the GPCET utilization in robust watermarking, this paper proposes a secondary grid-division (SGD)-based moment calculation method that divides each grid corresponding to one pixel into nonoverlapping subgrids and increases the number of sampling points. Using the accurate moment calculation method, a nonsubsampled contourlet transform (NSCT)–GPCET-based watermarking scheme with resistance to image processing and geometrical attacks is proposed. In this scheme, the accurate moment calculation can reduce the numerical error and geometrical error of the traditional methods, which is verified by an image reconstruction comparison. Additionally, NSCT and accurate GPCET are utilized to achieve watermark stability. Subsequent experiments test the proposed watermarking scheme for its invisibility and robustness, and verify that the robustness of the proposed scheme outperforms that of other schemes when its level of invisibility is significantly higher.

A Review on Watermarking using Local Binary Pattern

Local binary patterns are best known because of their robust texture-defining capacities and digital watermarking used to prove multimedia content copyright. This work presents an overview of the binary watermark in the image blocks by changing the pixels conveyed by the LBP pattern of the neighborhood. However, different photo blocks can have the same LBP pattern, which in the watermark process can lead to incorrect detection. In other words, without changing your watermark message, one can change the host image deliberately. Moreover, before watermark embedding, there is no encryption procedure, which leads to another potential security problem. In this paper, we examine the identical process of LBP synthesis or reverse LBP and its suitability for the digital watermarking image. The process of LBP synthesis varies by pixel values so that the LBP from these pixels is the required synthesizable value. Due to the LBP synthesis character, the watermark needs to be integrated with only a few pixels of the given block. The results show that rotational, JPEG compression, and scalable attacks are robust with the technique. This LBP synthesis could also be used to justify ownership using watermark sensor data.

A Novel Video Watermarking Algorithm using DTCWT

In this paper a new novel color video watermarking algorithm has been proposed using Dual Tree Complex Wavelet Transform (DTCWT). Digital watermarking is an emerging technology for copyright protection for digital multimedia data. Now-a-days a lot of digital data are exchanged in the internet, so to protect the digital multimedia data, digital watermarking is used, the data may be an image or video or an audio data. The main objective of this paper is to maintain perceptivity of digital video and design a robust watermarking algorithm and maintaining the tradeoff between robustness and perceptivity.

A Hidden DCT-Based Invisible Watermarking Method for Low-Cost Hardware Implementations

This paper presents an invisible and robust watermarking method and its hardware implementation. The proposed architecture is based on the discrete cosine transform (DCT) algorithm. Novel techniques are applied as well to reduce the computational cost of DCT and color space conversion to achieve low-cost and high-speed performance. Besides, a watermark embedder and a blind extractor are implemented in the same circuit using a resource-sharing method. Our approach is compatible with various watermarking embedding ratios, such as 1/16 and 1/64, with a PSNR of over 45 and the NC value of 1. After Joint Photographic Experts Group (JPEG) compression with a quality factor (QF) of 50, our method can achieve an NC value of 0.99. Results from a design compiler (DC) with TSMC-90 nm CMOS technology show that our design can achieve the frequency of 2.32 GHz with the area consumption of 304,980.08 μm2 and power consumption of 508.1835 mW. For the FPGA implementation, our method achieved a frequency of 421.94 MHz. Compared with the state-of-the-art works, our design improved the frequency by 4.26 times, saved 90.2% on area and increased the power efficiency by more than 1000 fold.

Novel quaternion polar complex exponential transform and its application in color image zero-watermarking

The robust watermarking method embeds the information in the image to protect the copyright. The embedding process will destroy the original image and cannot be effectively applied to the images used in the medicine and military with high integrity demand. A robust zero-watermarking algorithm for lossless copyright protection of color images without changing the original image was proposed in this paper. A novel quaternion polar complex exponential transform (NoQPCET) was firstly constructed with effectively improved performance; then the NoQPCET and chaotic system based robust color image zero-watermarking algorithm was suggested for lossless copyright protection of color images. In the proposed algorithm, the robustness against geometric attacks was enhanced due to the excellent geometric invariance of NoQPCET, and the security was also improved because of the initial value sensitivity of the chaotic system. Experimental results showed that this algorithm had very strong robustness against both geometric attacks and common image processing attacks, and was superior to other algorithms.

A Robust Watermarking Technique for High-Efficiency Video Coding (HEVC) Based on Blind Extraction Scheme

A Robust Watermarking Technique for High-Efficiency Video Coding (HEVC) Based on Blind Extraction Scheme

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.

Data Aggregation and Privacy Preserving Using Computational Intelligence

In today's smart world, the privacy protection of data is an important issue. Data is distributed, reproduced, and disclosed with extensive use of communication technologies. Many non-traditional challenges arise with the rapid increase of IoT devices for system design and implementation. However, security and privacy are the main issues in IoT. With advanced technologies, an illegal copy of the content can easily be generated and shared. Therefore, it is crucial for users to protect and secure their data. In the said perspective, an efficient third-generation watermarking technique is proposed, which works on the computational intelligence model to insert a large amount of robust watermark and make an extra effort to hide more information than first and second-generation techniques. The Advanced Encryption Standard (AES) encryption algorithm is employed to guarantee secure communication, which has a significantly less computational cost. The proposed technique evaluated parameters including security, robustness, imperceptibility, and capacity. The results of the proposed technique are compared to existing text watermarking methods, which illustrates it is secure, robust, imperceptible, and inserts a large amount of watermark information through computational intelligence.