Watermark Capacity Research Articles

Color image watermarking using a discrete trinion Fourier transform

A discrete trinion Fourier transform (DTFT) is proposed and computation of the DTFT is derived from the discrete Fourier transform. A block-based color image watermarking scheme is designed based on the proposed DTFT. The watermark bits are embedded by modifying the DTFT coefficients of each block by means of the quantization index modulation method. Finally, assessment of this watermarking approach is performed in terms of watermark capacity, invisibility, and robustness. A comparison with a quaternion discrete Fourier transform is also provided. Experimental results show that the proposed method is not only more robust in most standard attack situations, but also has superior time efficiency.

Identification of Sonar Detection Signal Based on Fractional Fourier Transform

Abstract Aiming at the source of underwater acoustic emission, in order to identify the enemy emission sonar source accurately. Using the digital watermarking technology and combining with the good time-frequency characteristics of fractional Fourier transform (FRFT), this paper proposes a sonar watermarking method based on fractional Fourier transform. The digital watermark embedding in the fractional Fourier transform domain and combined with the coefficient properties of the sonar signal in the fractional Fourier transform to select the appropriate watermark position. Using the different characteristics of the signals before and after embedding, an adaptive threshold was set for the watermark detection to realize the discrimination of sonar signals. The simulation results show the feasibility and has better resolution and large watermark capacity of this method, while the robustness of the watermark is better, and the detection precision is further improved.

Evaluating the topological quality of watermarked vector maps

The pervasive use and exchange of digital content led to increased efforts in the research community for efficient approaches to protect intellectual property rights. While watermarking techniques have been used extensively for raster image format, watermarking approaches for the vector map format have been largely inspired from existing image watermarking techniques, without due consideration to the suitability of these techniques for this different data format. A key requirement of any watermarking approach of vector data is the preservation of the topological quality of the watermarked data. This is sometimes referred to as the invisibility of the watermark. For vector map data, the topological quality and invisibility are fundamentally different, but currently submerged into one and measured with error metrics borrowed from image watermarking, such as Root Mean Squared Error (RMSE) and Peak Signal to Noise Ratio (PSNR). Over the last 10 year, the research community on watermarking vector map data has repeatedly posed that error metrics alone are not appropriate for the evaluation of watermarked vector map topological quality. In this paper, a metric for measuring topological quality by measuring topological distortions is proposed based on topological properties of polygon-based vector maps. To evaluate the proposed metric, experiments with controlled watermarking capacity (i.e. how much is embedded) were run on maps of various sizes, using two popular embedding approaches, i.e. coordinate-based and distance-based embedding. The results indicate that the metrics allow comparisons between watermarked maps of different sizes and of different watermark sizes, and, thus, can be used to assess the quality of watermarked vector maps. The advantages and limitations of the proposed metric are discussed and further research directions are highlighted toward an agreed metric by the research community.

Anti-HEVC Recompression Video Watermarking Algorithm Based on the All Phase Biorthogonal Transform and SVD

ABSTRACTWith the rapid development of Internet of Things and multimedia technologies, people are paying more attention to the security of images and videos. To further improve the security of video content, a video watermarking algorithm based on the high efficiency video coding (HEVC) compression domain is proposed in this paper. The scheme embeds watermark information in the quantized coefficients, which can solve the cumulative error caused by watermark embedding. Moreover, the all phase biorthogonal transform (APBT), an improved transform, is used to compress the watermark data at the digital watermark preprocessing stage, optimize the watermark embedding scheme, and improve the embedding capacity of video watermarking. Due to the characteristics of HEVC video coding, most HEVC video watermarking schemes based on compression domain cannot resist recompression attack. To solve this problem, on the basis of APBT and singular value decomposition, an anti-HEVC recompression video watermarking algorithm is proposed and can effectively resist the HEVC recompression. Experimental results show that even when the quantization parameter is larger than 40, the extracted watermark still has good image quality. In addition, the algorithm also has a good performance in noise resistance.

A Self-Recovery Fragile Image Watermarking with Variable Watermark Capacity

Currently, the watermark capacity of most self-recovery fragile image watermarking schemes is fixed. That means for smooth regions and texture regions, the length of watermark information is always the same. However, it is impractical since more recovery information is needed for the recovery of texture regions. In this paper, a self-recovery fragile image watermarking with variable watermark capacity is proposed. Based on the characteristic of singular value decomposition (SVD), a new block classification method is introduced. The image blocks are classified into smooth blocks and texture blocks. For smooth blocks, the average pixel values are adopted as the recovery information to recover the tampered blocks, while for texture blocks, the quantized and coded DCT coefficients are adopted as the recovery information. After encrypted by binary pseudo-random sequence, the recovery watermark of each block is embedded into its mapping block. In the detection side, the three-level detection mechanism is applied to detect and locate the tampered regions. The experimental results prove that the proposed method achieves good tamper detection results, and the recovered image has better image quality than other self-recovery fragile watermarking methods.

Reversible Data Hiding for DNA Sequence Using Multilevel Histogram Shifting

A large number of studies have examined DNA storage to achieve information hiding in DNA sequences with DNA computing technology. However, most data hiding methods are irreversible in that the original DNA sequence cannot be recovered from the watermarked DNA sequence. This study presents reversible data hiding methods based on multilevel histogram shifting to prevent biological mutations, preserve sequence length, increase watermark capacity, and facilitate blind detection/recovery. The main features of our method are as follows. First, we encode a sequence of nucleotide bases with four-character symbols into integer values using the numeric order. Second, we embed multiple bits in each integer value by multilevel histogram shifting of noncircular type (NHS) and circular type (CHS). Third, we prevent the generation of false start/stop codons by verifying whether a start/stop codon is included in an integer value or between adjacent integer values. The results of our experiments confirmed that the NHS- and CHS-based methods have higher watermark capacities than conventional methods in terms of supplementary data used for decoding. Moreover, unlike conventional methods, our methods do not generate false start/stop codons.

A multiple watermarking algorithm for vector geographic data based on coordinate mapping and domain subdivision

A lot of watermarking algorithms for vector geographic data are presented in the literature. Due to widely application of digital watermarking, more demands are required, such as multiple watermarking algorithm. However, vector geographic data attracted less research focus on multiple watermarking. Consequently, a multiple watermarking algorithm for vector geographic data is proposed. In particular, the vertices are mapped to the logic domains firstly based on the constructed function. Then every domain is subdivided into blocks according to dichotomy and the number of embedding watermarks. Then, every watermark is embedded in the corresponding block. During the watermark detection, the watermarks are detected without the original vector geographic data. Finally, the experiments are made to test the multiple watermark capacity and robustness against attacks, with an emphasis on cropping attacks. The experimental results show that the proposed algorithm has good robustness against common attacks, such as, data simplification, vertex addition, vertex deletion, feature deletion, and cropping attacks. Moreover, the algorithm provides high multiple watermark capacity.

Robust Reversible Watermarking Algorithm Based on RIWT and Compressed Sensing

In order to improve the robustness of existing reversible watermarking algorithms and strengthen the imperceptibility of watermarked images, a robust reversible watermarking algorithm based on redundant integer wavelet transform and compressed sensing is proposed. Firstly, the algorithm selects the high capacity embedding regions in the original image and then redundant integer wavelet transform is conducted within the selected areas, and wavelet coefficients matrices are obtained after the sparse. After that, the two intermediate-frequency parts of each wavelet coefficient matrix are conducted by compressed sensing with the same observation matrix, and the two generated compressed observation values are merged. Finally, the watermark is embedded into the observation value of intermediate-frequency coefficient part, to recover the sparse signal by using the reconstruction algorithm, and then the watermarked image is obtained through the redundant integer wavelet inverse transform. Simulation results indicate that the algorithm can not only realize blind extraction, but also significantly improve robustness, imperceptibility and embedded watermark capacity compared with other similar algorithms. It is easy to implement. What’s more, the generated watermarked images have high quality and can completely lossless restore the original carrier image without any attacks.

Geometric distortion correction based robust watermarking scheme in LWT-SVD domain with digital watermark extraction using SVM

With the advent of technology, digital image watermarking turns to be an effective technique to protect digital images from illegal usages and manipulation. In digital image watermarking, one of the major challenges is to provide robustness against geometrical attack maintaining adequate level of imperceptibility and security. In this work, a robust digital image watermarking scheme is proposed based on the combination of lifting wavelet transform(LWT) and singular value decomposition(SVD). To achieve better correlation between the extracted and original watermark, SVM-based binary classification approach is integrated in watermark extraction. In the proposed technique, geometric distortion correction based approach is incorporated with SVM based binary watermark detection to achieve improved robustness against de-synchronization attack. The 3-level LWT is performed on the cover image where horizontal (HL) sub-band is chosen for binary watermark insertion. The training and testing patterns are formed using an optimized set of features along with the singular values of corresponding blocks. In case of de-synchronization attacks, geometrical distortion correction is required before performing watermark extraction. In the detection process, the geometric distortion parameters of the attacked watermarked image are estimated by the geometric correction method. This algorithm provides high robustness against both the geometrical and non-geometrical attacks. It has been observed that the algorithm gives average imperceptibility of ~42.27 dB with the watermark capacity of 512 bits. Experimental results suggest that the proposed watermarking scheme provides significant improvement in terms of robustness and security of the watermark. The subjective analysis also suggests that proposed scheme provides improved performance over some of the recent existing techniques.

Non-blind digital watermarking with enhanced image embedding capacity using DMeyer wavelet decomposition, SVD, and DFT

Amongst the requirements of digital color image watermarking–capacity is the major component to be addressed effectively. To address the same we proposed a method for inserting a color image into another color image of same size using non-blind watermarking scheme. From this method we achieved reasonably good perceptual similarity by measuring acceptable peak signal to noise ratio (PSNR) and structural similarity (SSIM) index. The method uses DMeyer single level discrete wavelet transformation (DWT) to get approximation coefficients-where most of the image information is stored, discrete Fourier transformation (DFT) is used to get set of components which are sufficient to describe the whole image and singular value decomposition (SVD) to get reliable orthogonal matrix of computationally sustainable components of the transformed image. The method is robust against attacks like–rotation, cropping, JPEG compression and for noises–salt and pepper, gaussian, speckle.

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.

A New Reversible Database Watermarking Approach with Firefly Optimization Algorithm

Up-to-date information is crucial in many fields such as medicine, science, and stock market, where data should be distributed to clients from a centralized database. Shared databases are usually stored in data centers where they are distributed over insecure public access network, the Internet. Sharing may result in a number of problems such as unauthorized copies, alteration of data, and distribution to unauthorized people for reuse. Researchers proposed using watermarking to prevent problems and claim digital rights. Many methods are proposed recently to watermark databases to protect digital rights of owners. Particularly, optimization based watermarking techniques draw attention, which results in lower distortion and improved watermark capacity. Difference expansion watermarking (DEW) with Firefly Algorithm (FFA), a bioinspired optimization technique, is proposed to embed watermark into relational databases in this work. Best attribute values to yield lower distortion and increased watermark capacity are selected efficiently by the FFA. Experimental results indicate that FFA has reduced complexity and results in less distortion and improved watermark capacity compared to similar works reported in the literature.

Robust covert communication using high capacity watermarking

Generally, in watermarking techniques the size of the watermark is very small when compared to the host image. In other words, a little amount of watermark is embedded in the huge quantity of image pixels as the notice of legitimate ownership. Contrary to that idea, this is an attempt in which the capacity of watermarking is improved by embedding huge amount of watermark efficiently in the less quantity of image pixels. The core idea behind the proposed approach is to select watermarkable pixels from the host image based on the census transform and hamming distance followed by the embedding which is done by proposed spectral decompositions, i.e., Hankel, Circulant and Topelitz spectral decomposition. Finally, a reliable watermark extraction scheme is developed which is free from the false-positive detection problem of singular values. The experimental evaluation demonstrates that the proposed scheme is expeditiously able to withstand a variety of extreme attacks and highly suitable for covert communications.

An adaptive HVS based video watermarking scheme for multiple watermarks using BAM neural networks and fuzzy inference system

An efficient reversible adaptive video watermarking scheme for multiple watermarks based on Bi-directional Associative Memory (BAM) Neural Networks and Fuzzy Inference System namely, Multi-BAM-FUZ scheme is proposed in this paper. The main goal of this paper is to design a robust video watermarking system which facilitates secure video transmission over a communication channel by maintaining a trade-off among imperceptibility, robustness and watermark capacity or payload. The BAM neural network supports creation of weight matrix (formed out of multiple images) and this matrix is embedded into the DWT uncorrelated mid frequency coefficients of all the components (Y, Cb, Cr) of every frames of the video with varying embedding strength ‘α’. This adaptive embedding strength is generated using the Fuzzy Inference System which takes HVS characteristics such as luminance, texture and edge of each frame as an input in the DWT transform. The simulations performed on various test videos demonstrate that the proposed Multi-BAM-FUZ not only outperforms other existing methods with respect to various video degradation processes, but also maintains a satisfactory image quality, robustness and payload. It is noted that, the implementation of the novel adaptive process enhances the visual quality of about 60.97dB in terms of PSNR and 0.9998 in terms of SSIM, robustness of about nearly 1.0000 and 0.9999 in terms of Normalized Cross Correlation (NCC) value and Bit Correction Rate (BCR) respectively against various attacks. Moreover, the proposed scheme facilitates high level of payload without affecting the imperceptibility and robustness level.

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.

Adaptive reversible video watermarking based on motion-compensated prediction error expansion with pixel selection

In this study, a motion-compensated prediction error expansion-based adaptive reversible video watermarking algorithm is proposed. Blocks of motion-compensated frames are classified as smooth and non-smooth according to their prediction errors. Unlike the current reversible video watermarking methods that apply a single watermarking strategy to all blocks, the proposed method uses two different strategies for smooth and non-smooth blocks. This adaptive strategy is shown to increase watermarking capacity. In addition, an approach is suggested to detect those pixels causing high distortion in the watermarked video and they are not used in watermarking to limit the distortion occurring in the original video. Simulations show that the proposed method is superior to existing methods in terms of capacity and distortion.

Lossless embedding of depth hints in JPEG compressed color images

The conventional JPEG compressed domain lossless data hiding scheme has three attractive properties: file size is maintained, decoded image is unchanged, and embedded bitstream is compatible with the JPEG standard. This study introduces a new application of the compressed domain lossless data hiding scheme. Specifically, we present an algorithm that embeds depth hints to a compressed bitstream of a color image, which enables the end-user to extract depth hints and reconstruct the depth image. On the limited watermark capacity, depth hints are obtained using super-pixel color image segmentation and depth value clustering. The experimental results demonstrate the effectiveness of the proposed algorithm.

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.

Binocular visual characteristics based fragile watermarking scheme for tamper detection in stereoscopic images

In the past decade, various fragile digital watermarking techniques have been proposed for monoscopic image authentication and temper detection. In this paper, a novel binocular visual characteristics based pixel-wise fragile watermarking scheme for stereoscopic image authentication and tamper detection is proposed. The scheme consists of two processes: embedding of the stereoscopic image authentication message and tamper detection. In the watermark embedding process, the binocular just noticeable difference (BJND) model is used for guiding watermark embedding, which is convenient for achieving a balanced relationship between watermarking capacity and visual transparency. In the tamper detection process, a probability theory and an algorithm of binocular disparity are employed to improve previously obtained detection results and to enhance authentication accuracy. Moreover, to improve the security of the proposed scheme, MD5 hash function and chaotic map are used. Experimental results reveal that the proposed scheme is not only secure, but also achieves superior tamper detection for different attacks.