Adaptive Image Watermarking Research Articles

Image-adaptive watermarking using maximum likelihood decoder for medical images

In this paper, a new medical image-adaptive watermarking technique is proposed in which embedding of the watermark is done in low frequency coefficients for achieving high robustness using an adjustable dynamic strength factor. The low frequency coefficients are modeled using Gaussian distribution to design a Maximum Likelihood (ML) decoder. The decoder recovers the watermark with the help of side information containing the adjustable dynamic strength factor, position of blocks (used for embedding), mean and variances of low frequency coefficients. The method contributes towards a highly flexible and easily adjustable dynamic strength factor for achieving the best imperceptibility with the highest robustness. The validity of the new technique is verified against various attacks and the results are compared with other watermarking schemes. The proposed technique is found to generate better results.

Quaternion discrete fractional random transform for color image adaptive watermarking

As for the fractional transforms, to date only fractional Fourier transform (FrFT) has been applicable to color images in a holistic manner by using the quaternion algebra, yet, discrete fractional random transform (DFRNT) with the useful intrinsic randomness is still to be explored. This paper first defines quaternion DFRNT (QDFRNT) which generalizes DFRNT to efficiently process quaternion signals, and then applies QDFRNT to color image adaptive watermarking. For the QDFRNT, this paper also derives the relationship between QDFRNT of a quaternion signal and DFRNT of four components for this signal to efficiently compute QDFRNT. For the color image adaptive watermarking based on QDFRNT and SVM, in order to efficiently utilize the color information in the adaptive process, this paper also exploits the human vision system’s (HVS) masking properties of texture, edge and color tone directly from the color host image to adaptively adjust the watermark strength for each block. In addition, the constraints in watermark embedding are discussed to preserve the watermarking energy. Experimental results show that: (a) the proposed efficient computation method takes only half the computational time of the direct method; (b) the comparison of five color models (RGB, YUV, YIQ, CIEL*a*b* and YCbCr) shows that the proposed QDFRNT-based watermarking scheme using YCbCr color model has the overall best performance and can achieve a good balance between invisibility and robustness to the Checkmark attacks; (c) The proposed scheme is superior to the existing schemes respectively using DCT, DFRNT, discrete quaternion Fourier transform (DQFT), discrete fractional quaternion Fourier transform (DFrQFT), and quaternion radial moments (QRMs). Moreover, the fractional order and the random matrix of QDFRNT enhance the security of the proposed scheme.

A Blind Adaptive Color Image Watermarking Scheme Based on Principal Component Analysis, Singular Value Decomposition and Human Visual System

A Blind Adaptive Color Image Watermarking Scheme Based on Principal Component Analysis, Singular Value Decomposition and Human Visual System

Image Adaptive Watermarking Using Feature Point Extraction Model

Image Adaptive Watermarking Using Feature Point Extraction Model

A new region aware invisible robust blind watermarking approach

The multimedia revolution has made a strong impact on our society. The explosive growth of Internet access to this digital information has generated new opportunities and challenges. The ease of editing and duplicating information in the digital domain has created copyright protection concerns for content providers. Various schemes to embed secondary data in digital media have been investigated to preserve copyright and to discourage unauthorized duplication. In order to achieve the required level of protection to digital information, digital watermarking is a viable solution. This paper proposes a novel invisible watermarking scheme: a Discrete Cosine Transform (DCT) domain based watermark embedding and blind extraction algorithm for copyright protection of color images. The proposed algorithm is optimized in terms of robustness, computational load, and quality of the image. Testing of the proposed watermarking scheme’s robustness and security via different benchmarks as well as comparison with a Discrete Wavelet Transform (DWT) approach proves its resilience to digital attacks. The results show that the Peak Signal to Noise Ratio (PSNR) value obtained under no attack conditions in the proposed algorithm is above 41.81 dB, which is higher than most of the existing watermark algorithms. The results from the detector’s response also show that the proposed algorithm has a better security performance than most of the existing algorithms. The architecture for hardware implementation of the proposed algorithm is also presented and the results from the architecture show a PSNR value of 44.37 dB. This verifies that the presented algorithm is more effective than existing algorithms such as image adaptive watermarking, image adaptive watermark creation, zerotree wavelet, and 9/7 biorthogonal wavelet lifting.

Fuzzy knowledge-based adaptive image watermarking by the method of moments

A novel adaptive image watermarking methodology, robust to common signal processing attacks, is proposed in this paper. The introduced watermarking scheme uses prior knowledge in the form of IF–THEN fuzzy rules to intelligently decide the appropriate embedding strength applied to each coefficient in the moment domain carrying the watermark information. Initially, the prior knowledge regarding the amount of watermark information each moment coefficient of the original image has the capacity to hide is used to build an optimized rule-based fuzzy inference system. The resulted system is able to provide the appropriate embedding strength for each moment coefficient, ensuring high imperceptible watermarked images and high fidelity in watermark extraction. Extensive experiments under several attacking conditions demonstrate that the proposed methodology can improve the robustness of the watermarked images by a significant factor up to 32 %, without affecting their optical quality.

Adaptive Image Watermarking Scheme Using Fuzzy Entropy and GA-ELM Hybridization in DCT Domain for Copyright Protection

A novel semi-blind image watermarking scheme based on fuzzy entropy and genetic algorithm (GA)--extreme learning machine (ELM) hybridization in discrete Cosine transform (DCT) domain for copyright protection is proposed in this paper. The selection of non overlapping blocks to embed the binary watermark is based on fuzzy entropy. As fuzzy entropy is able to discriminate data distribution under noise corrupted and redundant condition, feature extraction is more robust against various attacks. Each selected block is followed by 2-D DCT to transform it from spatial to frequency domain. Low frequency coefficients have good energy compactness and are robust to image processing attacks. As addition of noise corresponds to high frequency coefficients, these are not considered to embed the watermark in the proposed approach. The optimal scaling factor used to control the strength of watermark for each selected block of the image based on its noise sensitivity and tolerance limit is determined using GA optimization process. ELM is used to find an optimal regression function between the input feature vector (low frequency DCT coefficients) and corresponding target vector (in which the watermark bits are embedded) of each selected block. Then watermark embedding and extraction is performed intelligently by the regression function obtained by the trained ELM. The experimental results show that the proposed scheme is highly imperceptible and robust to geometric and non geometric attacks such as JPEG compression, filtering, noise addition, sharpening, gamma correction, scaling and cropping etc. To demonstrate the effectiveness of the proposed scheme, comparison with the state-of-art techniques clearly exhibits its applications for copyright protection.

A Kind of DWT Domain Image Digital Watermarking Algorithm Research

An image-adaptive watermarking algorithm based on wavelet transform was proposed. At first, A digital image used as watermarking was scrambled. Next, the original image was decomposed by discrete wavelet transform,and in accordance with the characteristics of human visual system, wavelet decomposition in the low-frequency domain, Methods which average of adjacent domain instead of single wavelet decomposition coefficients was used to estimate and quantitative, watermarking was adaptively embedded in wavelet coefficients of low-frequency domain. At last, the simulation experimental results show that the algorithm for a variety of conventional image processing has good robustness.

Image adaptive and high‐capacity watermarking system using accurate Zernike moments

The authors propose a novel image adaptive watermarking scheme for geometrically invariant and high-capacity data embedding scheme based on accurate and fast framework for the computation of Zernike moments (ZMs). The high capacity is achieved by maximising data embedding size and improving the hiding ratio after reducing the inaccuracies in the computation of ZMs. Furthermore, they also introduce a concept of conditional quantisation technique which enables to reduce the total number of ZMs needed to be modified during watermark embedding. This concept enhances the visual imperceptibility of the watermarked image and its robustness against various attacks. Numerous experiments have been performed to demonstrate the improvements in embedding capacity, visual imperceptibility, watermark robustness and time complexity as compared with the existing methods.

Adaptive color image watermarking by the use of quaternion image moments

The first adaptive moment-based color image watermarking is presented in this work. The proposed method exploits rotation invariance, high reconstruction capability and computation accuracy of the quaternion radial moments’ (QRMs), subject to the tradeoff between robustness and imperceptibility. The current system manages to multi-embed binary logos to color images applying QRMs as information carriers. A novel adaptive system adjusts the watermark’s embedding strength (online) by taking into account image’s morphology, with respect to robustness and imperceptibility. The method manages to experimentally justify and further eliminate the attack-free phenomenon that state-of-the-art methods suffer. The simulation results justified that the proposed framework manages to highly secure its carrying information under common signal processing and geometric attacking conditions. Furthermore, the adoption of the novel adaptive process enhances the robustness and imperceptibility requirements by reducing the Bit Error Rate even by 49% and producing even 5db higher PSNR values, respectively.

Robust image-adaptive watermarking using an adjustable dynamic strength factor

This paper presents a novel spread spectrum based image-adaptive watermarking technique where selective embedding of watermark has been done in small building blocks of the image, depending upon the respective entropies of the blocks. Novelty of this method lies in the flexibility of its strength factor which can be adjusted easily in order to obtain a required level of visual quality of the watermarked image in terms of PSNR. Easy adjustability of the strength factor has helped in experimentally demonstrating the inverse relationship between imperceptibility and robustness of the watermark. Positions of embedded blocks, means of low-frequency wavelet coefficients and size of watermark have been used as side information for decoding of the watermark. Applied technique has shown exceptional resistance to some of the common watermarking attacks such as JPEG compression, median filtering, Gaussian filtering and AWGN noise attacks.

Perceptually adaptive MC-SS image watermarking using GA-NN hybridization in fading gain

This paper proposes an optimized multicarrier (MC) spread spectrum (SS) image watermarking scheme using hybridization of genetic algorithms (GA) and neural networks (NN). Data embedding is done in the mutually independent host components using the distinct code patterns that are assigned to the different watermark bits. GA determines the gradient thresholds for the pixel intensities to partition the host image into the edge, the smooth, and the texture regions as well as determines the watermark embedding strengths. The goal is to optimize the imperceptibility and the data hiding capacity. A minimum mean square error combining (MMSEC) decoder is used and the weight factors are calculated using NN through training/learning. Stable decision variables thus obtained for the watermark bit detection are partitioned into the multiple groups to improve decoder performance by canceling out the multiple bit interfering effect. Simulation results show the relative performance gain achieved in this method compared to the existing other works including the biologically inspired approaches.

Bi-orthogonal Wavelet based Adaptive Image Watermarking using Human Visual System and Fuzzy Inference System

Digital age today has shown increasing reliance on digital media and rapid distribution of digital contents. The issues of piracy and copyright are of immense concern in this exponentially increasing digital revolution. In this paper, authors propose use of bi-orthogonal wavelet transform as an effective tool to address copyright infringement issues. A synergistic combination of bi-orthogonal wavelet transform, human visual system characteristics and fuzzy inference system is arrived at to develop a novel adaptive image watermarking scheme. Logo watermark is used to prove ownership of digital property. A hierarchical data structure is generated using bi-orthogonal wavelet decomposition to represent an image. The reconstruction of image is achieved by computing inverse wavelet transform of modified wavelet coefficients. The unique feature of the proposed scheme is that fuzzy inference system is used to effectively establish relation between different HVS characteristics and adaptively adjusting embedding strength of watermark. General Terms Image Watermarking

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.

Rightful ownership through image adaptive DWT-SVD watermarking algorithm and perceptual tweaking

In this paper, a tailored blended image adaptive watermarking scheme has been presented, which is based on DWT and SVD. Through this paper an attempt has been made to solve the problem of false positive while maintaining the robustness and imperceptibility with the help of principal component and perceptual tuning of the image. Perceptual tuning is a non-blind technique and based on the objective quality of image. The embedding strength is made dependent on watermark features as well as of host in wavelet domain by using tuning parameter which is user specific. The idea of embedding the principal component of intermediate frequency sub-bands of watermark image into singular values of perceptually tuned intermediate frequency sub-bands of host image have been exploited. The proposed algorithm is providing the adaptive behavior towards the image content for perceptual transparency and at the same time avoiding the possibility of false watermark extraction well supported by a private key, which is necessary at the time of extraction. Thus the proposed watermarking algorithm is a kind of non-blind, image adaptive and suitable for rightful ownership. Various comparative results make the algorithm superior in terms of intentional and non-intentional attacks. Also the algorithm is strong against the print and scan attack.

Internet as Indispensable Everywhere: The Introduction to the Advances in Internet Technologies and Applications Special Issue

Internet as Indispensable Everywhere: The Introduction to the Advances in Internet Technologies and Applications Special Issue

Blind Adaptive Watermarking Based on Wavelet Transform and HVS

This paper proposes a novel blind image adaptive watermarking scheme in Discrete Wavelet Transform (DWT) domain for copyright protection or robust tagging applications. Watermarking scheme effectively utilizes the contrast sensitivity model of Human Visual System (HVS) to embed the watermark adaptively without degradation of the original image. Watermark can be extracted without referring to the original image. Simulation results show the robustness of the proposed algorithm against various attacks.

Block-based Adaptive Image Watermarking Scheme using Visual Perception Model in DCT Domain

ABSTRACT In this paper, an improved DCT-based watermarking technique has been presented, which exploits human visual model for adapting the watermark data to local properties of the host image. In order to achieve more robustness and transparency, watermark has been embedded into the middle frequency components of the image. These components are significant in high textural regions so that the visibility of the image would not be affected and the watermark will not be removed by compression. Experimental results are provided to demonstrate that embedded watermarks can be almost fully extracted from the JPEG-compressed images with very high compression ratios and other kind of attacked images.

Adaptive color image watermarking based on the just noticeable distortion model in balanced multiwavelet domain

In this paper, a novel adaptive color image watermarking scheme based on the just noticeable distortion (JND) model in balanced multiwavelet domain is proposed. The balanced multiwavelet transform can achieve orthogonality, symmetry, and high order of approximation simultaneously without requiring any input prefiltering, which makes it a good choice for image processing. According to the properties of the human visual system, a novel multiresolution JND model is proposed in balanced multiwavelet domain. This model incorporates the spatial contrast sensitivity function, the luminance adaptation effect, and the contrast masking effect via separating the sharp edge and the texture. Then, based on this model, the watermark is adaptively inserted into the most distortion tolerable locations of the luminance and chrominance components without introducing the perceivable distortions. Experimental results show that the proposed watermarking scheme is transparent and has a high robustness to various attacks such as low-pass filtering, noise attacking, JPEG and JPEG2000 compression.

SVD-Based Color Image Watermarking Using Discrete Wavelet Transform

For invisibility and robustness are difficult to reconcile, a combination of singular value decomposition (SVD) and the discrete wavelet transform (DWT) of the color image adaptive watermarking algorithm is proposed. In the embedding process, modification of the singular value of LL band and LH band exploited to the watermarking scheme which excellent preserves the quality. The additional advantage of the proposed technique is taking advantage of HVS which can adaptively regulate the watermark embedding strength. Experimental results show that the algorithm not only has better transparency, but also has good robustness such as noise, compression, filtering, cropping.