High-capacity Watermarking Research Articles

3D Object Watermarking from Data Hiding in the Homomorphic Encrypted Domain

For over a decade, 3D objects are an increasingly popular form of media. It has become necessary and urgent to secure them during their transmission or archiving. In this article, we propose a new method to obtain a watermarked 3D object from high-capacity data hiding in the encrypted domain. Based on the homomorphic properties of the Paillier cryptosystem, our proposed method allows us to embed several secret messages in the encrypted domain with a high-capacity. These messages can be extracted in the plain-text domain after the 3D object decryption. To the best of our knowledge, we are the first to propose a data hiding method in the encrypted domain where the high-capacity watermark is conserved in the plain-text domain after the 3D object is decrypted. The encryption and the data hiding in the encrypted domain are format compliant and without size expansion, despite the use of the Paillier cryptosystem. Each time a new message is embedded in the encrypted domain, flags are added in order to indicate which blocks are still available for the embedding of additional messages. After the decryption of a watermarked encrypted 3D object, our method produces a watermarked 3D object which is visually very similar to the original 3D object. From the decrypted watermarked 3D object, we can then extract all the embedded messages directly in the plain-text domain, without the need for an auxiliary file. Moreover, large keys are used, rending our method secure for real-life applications.

A robust and high embedding capacity watermarking technique for telemedicine

ABSTRACT The medical field has been greatly influenced by the rapid expansion of technology and globalization. Medical images are routinely transferred by wired or remote media amongst professionals, medical experts, analysts, and patients themselves in order to improve the diagnostic outcomes. To achieve investigative conclusions, physicians concentrate on the ROI (Region of Interest) in a medical image. To retrieve the ROI when it has been damaged by noise or altered by intruders during transmission, the ROI data are hidden within the RONI (Region of Non-Interest) in medical images. This paper intends a high embedding capacity watermarking system grounded on Finite Ridgelet Transform (FRT). Proposed method supports the high embedding capacity for concealing entire ROI data inside RONI and simultaneously provides a high level of robustness to the concealed data.

A high-capacity QRD-based blind color image watermarking algorithm incorporated with AI technologies

In this study, a high-capacity QR decomposition (QRD) based blind watermarking algorithm with artificial intelligence (AI) technologies for color images was proposed. Watermarking implementation involves dividing the host image into non-overlapping blocks of size 4 × 4 pixels and then applying the QRD to each block. Within each block, a two-bit watermark can be embedded by manipulating the relationship between paired elements drawn from the first column of the orthogonal matrix in the ORD. Through orthonormal restoration and iterative regulation, a perfect watermark retrieval can be guaranteed in the absence of image attacks. On top of the high-capacity watermarking, the proposed algorithm also exploits two AI technologies, namely, particle swarm optimization (PSO) and super-resolution convolutional neural network (SRCNN). The PSO seeks the optimal parameters for enhancing the imperceptibility and robustness, while the SRCNN facilitates the visual recognition of extracted watermarks. In comparison with previous matrix decomposition-based watermarking algorithms, the proposed algorithm exhibits a superior performance in imperceptibility and robustness while operating at the rate of 1/8 bit per pixel. Moreover, the SRCNN refinement contributes an improvement of 0.191 to image quality in terms of mean structural similarity index measure (MSSIM).

Chaotic Reversible Watermarking Method Based on IWT with Tamper Detection for Transferring Electronic Health Record

Health IoT deals with sensitive medical information of patients, therefore security concerns need to be addressed. Confidentiality of Electronic Health Record (EHR) and privacy are two important security requirements for IoT based healthcare systems. Recently, watermarking algorithms as an efficient response to these requirements is in the spotlight. Further, as smart city-based applications have to react to real-time situations, efficient computation is a demand for them. In this paper, a secure, lightweight, reversible, and high capacity watermarking algorithm with tamper detection capability is proposed for IoT based healthcare systems. The scheme has applied Integer Wavelet Transform (IWT) and chaotic map for efficiency and increasing security. EHR is encrypted and then embedded into the Least Significant Bits (LSB) of wavelet coefficients of medical images. The proposed method has been extensively tested for various color and grayscale commonly used medical and general images. Investigations on experimental results and criterions such as Peak Signal to Noise Ratio (PSNR) and Bit Error Ratio (BER) above 45.41 dB and 0.04, respectively, for payload of 432,538 bits indicate that the proposed method, besides providing security, being reversible, tamper detection capability, and high embedding capacity, has high imperceptibility and adequate resistance against different types of attacks.

Robust High-Capacity Watermarking Over Online Social Network Shared Images

In recent years, online social networks (OSNs) have become extremely popular and been one of the most common ways for storing and distributing images. Naturally, such widespread availability of OSN makes it a viable channel for transmitting additional data along with the image sharing. However, various lossy operations, e.g., resizing and compression, conducted by OSN platforms impose great challenges for designing a robust watermarking scheme over OSN shared images. In this paper, we tackle this challenge and propose a robust high-capacity watermarking technique, by using Facebook as a representative OSN. To achieve the satisfactory robustness, we first probe into Facebook and recover the image manipulation mechanism via a deep convolutional neural network (DCNN) approach. Assisted with the precise knowledge on the lossy channel offered by Facebook, we then suggest a DCT-domain image watermarking method that is highly robust against the lossy operations on Facebook, even without any error correcting codes (ECC). The proposed technique is also extended to other popular OSNs, e.g., Wechat and Twitter. Extensive experimental results are provided to show the superior performance of our method in terms of the embedding capacity, data extraction accuracy, and quality of the reconstructed images.

High-Capacity and Robust Watermarking Scheme for Small-Scale Vector Data

High-Capacity and Robust Watermarking Scheme for Small-Scale Vector Data

A High Capacity Watermarking Technique for the Printed Document

Digital watermarking technology is an effective method for copyright protection of digital information, such as images, documents, etc. In this paper, we propose a high capacity text image watermarking technique against printing and scanning processes. Firstly, this method obtains the invariant in the process of printing and scanning under the mathematical hypothesis model of print-scan transformation. Then based on the print-scan invariant, the Fourier descriptor is used to flip the trivial pixel points with high frequency information on the character boundary. Next, considering the resolution of the print-scan equipment and its influence on the print-scan invariant, a quadratic quantization function is proposed to embed watermark information of multiple bits for a single character. Finally, the QR code (Quick Response code) is researched, which has large information capacity, robust error correction ability and high decoding reliability. By using the QR code as the watermark information, we can reduce the impact of bit error rate during watermark extraction, and the robustness of the watermark information can be improved. The experimental results show that the proposed text watermarking algorithm has the advantages of anti-print scanning, anti-scaling, large capacity and good visual effects.

A Lossless Watermarking for 3D STL Model Based on Entity Rearrangement and Bit Mapping

With the wide application of 3D STL model in 3D printing, much attention has been paid to its content security and copyright protection. Based on entity rearrangement and bit mapping, a lossless and high capacity watermarking scheme is proposed for 3D STL model. Experimental results and analysis show that the average capacity is improved 0.71bits/facet compared with the original entity rearrangement method, and the capacity is 0.247 bits/entity larger than that of the optimal capacity of the standard entity rearrangement method. It can achieve good efficiency and it is robust against translation, rotation and even scaling. It has potential application in secret communication and copyright protection of 3D STL model.

Speech Content Authentication Scheme based on High-Capacity Watermark Embedding

The existed content authentication schemes based on digital watermark have some shortcomings. In order to solve the problems, a speech content authentication scheme based on high-capacity watermark embedding is proposed, and the high-capacity embedding method is discussed. Firstly, speech signal is framed and segmented, and the samples of each segment are scrambled. Secondly, DCT is performed on the scrambled signal, and low-frequency coefficients are selected as the watermark embedding domain. Lastly, frame number is mapped to a sequence of integers and embedded into the domain based on the embedding method. Theoretical analysis and experimental evaluation results show that the proposed algorithm is inaudible, robust to desynchronous attacks, enhances the embedding capacity, and improves the security of watermark system.

Intelligent Watermarking for High-Capacity Low-Distortion Data Embedding

Image watermarking intends to hide secret data for the purposes of copyright protection, image authentication, data privacy, and broadcast monitoring. The ultimate goal is to achieve highest embedding capacity and lowest image distortion. In this paper, we present an intelligent watermarking scheme which can automatically analyze an image content to extract significant regions of interest (ROIs). A ROI is an area involving crucial information, and will be kept intact. The remaining regions of non-interest (RONIs) are collated for embedding watermarks, and will be ranked according to their entropy fuzzy memberships into a degree of importance. They are embedded by different amounts of bits to achieve optimal watermarking. The watermark is compressed and embedded in the frequency domain of the image. Experimental results show that the proposed technique has accomplished high capacity, high robustness, and high PSNR (peak signal-to-noise ratio) watermarking.

Robust, Secure and High Capacity Watermarking Technique based on Image Partitioning-Merging Scheme

This paper presents secure and high capacity watermarking technique using novel approach of Image Partitioning-Merging Scheme (IPMS). The IPMS is used as reduction method to reduce the size of watermark logically and increases security levels of proposed watermarking technique. The technique effectively uses special properties of Discrete Wavelet Transform (DWT), Fast Walse Hadamrd Transform (FWHT), Singular Value Decomposition (SVD) and proved strongly robust to 14 noise addition and filtering attacks. Fibonacci Lucas Transform (FLT) is used as effective scrambling technique to scramble the watermark to provide additional security in embedding process. Many researchers failed to achieve imperceptibility and robustness under high watermark embedding scenario with strong security provision as these quality parameters conflict each other. The novel technique presented here archives imperceptibility, high capacity watermark embedding, security and robustness against 14 noise addition and filtering attacks. The technique is non-blind and tested with grey scale cover images of size 512x512 and watermark images of size 512x512. The experimental results demonstrate that Lena image gives 75.8446dBs imperceptibility which is measured in terms of Peak signal to noise ratio. The robustness is measured in terms of normalized correlation (NC) equals to 1 showing exact recovery of watermark. The method is found strongly robust against noise addition and filtering attacks with compared to existing watermarking methods under consideration.

High-capacity watermarking of high dynamic range images

High dynamic range (HDR) imaging techniques address the need to capture the full range of color and light that the human eyes can perceive in the real world. HDR technology is becoming more and more pervasive. In fact, most of the cameras and smartphones available on the market are capable of capturing HDR images. Among the challenges posed by the spread of this new technology there is the increasing need to design proper techniques to protect the intellectual property of HDR digital media. In this paper, we speculate about the use of watermarking techniques to cope with the peculiarities of HDR media to prevent the misappropriation of HDR images.

Robust high-capacity watermarking scheme based on Euclidean norms and quick coefficient alignment

This paper proposes simple but robust digital watermarking for color images based on Euclidean norms and quick coefficient alignment. For increasing the amount of hidden storage, we embedded two da...

Spread Spectrum-Based High Embedding Capacity Watermarking Method for Audio Signals

Audio watermarking is a promising technology for copyright protection of audio data. Built upon the concept of spread spectrum (SS), many SS-based audio watermarking methods have been developed, where a pseudonoise (PN) sequence is usually used to introduce security. A major drawback of the existing SS-based audio watermarking methods is their low embedding capacity. In this paper, we propose a new SS-based audio watermarking method which possesses much higher embedding capacity while ensuring satisfactory imperceptibility and robustness. The high embedding capacity is achieved through a set of mechanisms: embedding multiple watermark bits in one audio segment, reducing host signal interference on watermark extraction, and adaptively adjusting PN sequence amplitude in watermark embedding based on the property of audio segments. The effectiveness of the proposed audio watermarking method is demonstrated by simulation examples.

Large-Capacity Reversible Watermarking Algorithm for Medical Image Based on Block Histogram of Difference

This paper proposes a high-capacity reversible watermarking algorithm for medical image analysis based on the difference block histogram, which will benefit the medical image authentication and doctor–patient confidentiality. By dividing the original medical image into blocks, the method displaces the peak point of a block's histogram of difference and embeds multi-bit information at 1 pixel point. In so doing, secret communication and storage of large-capacity invisible medical diagnoses and patients personal confidential data can be achieved. Once the watermark is extracted, not only the image integrity is authenticated, but also the original image and personal data of the patient can be recovered in a nondestructive way. With low computational complexity, a high embedding capacity and little demand for auxiliary information, the proposed algorithm is highly secure and practical.

MEO based secured, robust, high capacity and perceptual quality image watermarking in DWT-SVD domain.

The aim of this paper is to present multiobjective evolutionary optimizer (MEO) based highly secured and strongly robust image watermarking technique using discrete wavelet transform (DWT) and singular value decomposition (SVD). Many researchers have failed to achieve optimization of perceptual quality and robustness with high capacity watermark embedding. Here, we achieved optimized peak signal to noise ratio (PSNR) and normalized correlation (NC) using MEO. Strong security is implemented through eight different security levels including watermark scrambling by Fibonacci-Lucas transformation (FLT). Haar wavelet is selected for DWT decomposition to compare practical performance of wavelets from different wavelet families. The technique is non-blind and tested with cover images of size 512x512 and grey scale watermark of size 256x256. The achieved perceptual quality in terms of PSNR is 79.8611dBs for Lena, 87.8446 dBs for peppers and 93.2853 dBs for lake images by varying scale factor K1 from 1 to 5. All candidate images used for testing namely Lena, peppers and lake images show exact recovery of watermark giving NC equals to 1. The robustness is tested against variety of attacks on watermarked image. The experimental demonstration proved that proposed method gives NC more than 0.96 for majority of attacks under consideration. The performance evaluation of this technique is found superior to all existing hybrid image watermarking techniques under consideration.

DNA-LCEB: a high-capacity and mutation-resistant DNA data-hiding approach by employing encryption, error correcting codes, and hybrid twofold and fourfold codon-based strategy for synonymous substitution in amino acids.

Data-hiding in deoxyribonucleic acid (DNA) sequences can be used to develop an organic memory and to track parent genes in an offspring as well as in genetically modified organism. However, the main concerns regarding data-hiding in DNA sequences are the survival of organism and successful extraction of watermark from DNA. This implies that the organism should live and reproduce without any functional disorder even in the presence of the embedded data. Consequently, performing synonymous substitution in amino acids for watermarking becomes a primary option. In this regard, a hybrid watermark embedding strategy that employs synonymous substitution in both twofold and fourfold codons of amino acids is proposed. This work thus presents a high-capacity and mutation-resistant watermarking technique, DNA-LCEB, for hiding secret information in DNA of living organisms. By employing the different types of synonymous codons of amino acids, the data storage capacity has been significantly increased. It is further observed that the proposed DNA-LCEB employing a combination of synonymous substitution, lossless compression, encryption, and Bose-Chaudary-Hocquenghem coding is secure and performs better in terms of both capacity and robustness compared to existing DNA data-hiding schemes. The proposed DNA-LCEB is tested against different mutations, including silent, miss-sense, and non-sense mutations, and provides substantial improvement in terms of mutation detection/correction rate and bits per nucleotide. A web application for DNA-LCEB is available at http://111.68.99.218/DNA-LCEB.

Wavelet-based high-capacity watermarking of 3-D irregular meshes

Digital watermarking can be used as data hiding technique to interleave cover content with auxiliary information before transmitting and storing applications. While image and video watermarking has been widely studied, much less attention has been paid to its application in 3D mesh models. This is principally due to their intrinsic irregular sampling nature. This paper proposes a high-capacity watermarking scheme for the purpose of inserting meta-data into 3D triangle meshes. Our proposal can be applied to meshes with arbitrary topology by using irregular wavelet-based analysis. The watermark is embedded in an appropriate resolution level by quantizing the norms of wavelet coefficient vectors. To ensure robustness to similarity transformation, a robust synchronization (indexing) mechanism is performed on the 3D model after irregular wavelet analysis. Experimental results show that our watermarking framework is robust to common geometric attacks and can provide relatively high data embedding rate whereas keep a relative lower distortion.

A high capacity image adaptive watermarking scheme with radial harmonic Fourier moments

In this paper, we introduce a novel image adaptive technique for high capacity watermarking scheme using accurate and fast radial harmonic Fourier moments (RHFMs). The high embedding capacity is achieved by improving the hiding ratio after reducing inaccuracies in the computation of RHFMs. The binary watermark is embedded by performing the conditional quantization of selected RHFMs magnitudes to minimize the spatial distortion added to the host image. In addition, fast algorithms based on 8-way symmetry/anti-symmetry properties and recursive relations for the computation of sinusoidal kernel functions are adopted to enhance the speed of RHFMs-based watermarking process. Experimental studies show that the proposed watermarking scheme provides higher embedding capacity, good visual imperceptibility, better robustness to geometric distortions and common signal processing transformations, and lower computational complexity compared to the existing Zernike and pseudo-Zernike moments (ZMs/PZMs)-based watermarking schemes.

A robust high-capacity affine-transformation-invariant scheme for watermarking 3D geometric models

In this article we propose a novel, robust, and high-capacity watermarking method for 3D meshes with arbitrary connectivities in the spatial domain based on affine invariants. Given a 3D mesh model, a watermark is embedded as affine-invariant length ratios of one diagonal segment to the residing diagonal intersected by the other one in a coplanar convex quadrilateral. In the extraction process, a watermark is recovered by combining all the watermark pieces embedded in length ratios through majority voting. Extensive experimental results demonstrate the robustness, high computational efficiency, high capacity, and affine-transformation-invariant characteristics of the proposed approach.