scholarly journals NSCT Domain Additive Watermark Detection Using RAO Hypothesis Test and Cauchy Distribution

2016 ◽  
Vol 2016 ◽  
pp. 1-18 ◽  
Author(s):  
Hongbo Bi ◽  
Ying Liu ◽  
Mengmeng Wu ◽  
Yanliang Ge
Keyword(s):  
Spread Spectrum ◽  
Hypothesis Test ◽  
Image Watermarking ◽  
Random Noise ◽  
Cauchy Distribution ◽  
The Other ◽  
Lower Probability ◽  
Probability Of False Alarm ◽  
Low Pass ◽  
Watermarking Scheme

We presented a RAO hypothesis detector by modeling Cauchy distribution for the Nonsubsampled Contourlet Transform (NSCT) subband coefficients in the field of additive spread spectrum image watermarking. Firstly, the NSCT subband coefficients were modeled following the Cauchy distributions, and the Fit of Goodness shows that Cauchy distribution fits the NSCT subband coefficients more accurately than the Generalized Gaussian Distribution (GGD) commonly used. Secondly, a blind RAO test watermark detector was derived in the NSCT domain, which does not need the knowledge of embedding strength at the receiving end. Finally, compared to the other three state-of-art detectors, the robustness of the proposed watermarking scheme was evaluated when the watermarked images were attacked by JPEG compression, random noise, low pass filtering, and median filtering. Experimental results show that, compared with the other three detectors, the proposed RAO detector guarantees the lower probability of miss under the given probability of false alarm.

Watermarking Techniques for DRM Applications

2009 ◽  
pp. 71-100
Author(s):  
Alessandro Piva ◽  
Roberto Caldelli ◽  
Alessia De Rosa ◽  
Mauro Barni ◽  
Vito Cappellini
Keyword(s):  
Digital Watermarking ◽  
Digital Image ◽  
Spread Spectrum ◽  
Image Watermarking ◽  
Mathematical Formulation ◽  
Multimedia Content ◽  
Practical Implementation ◽  
Digital Image Watermarking ◽  
Spread Spectrum Watermarking ◽  
Watermarking Scheme

The need to safeguard the property rights of multimedia content from unauthorized copying and the possibility to determine the true owners of the asset can be faced by resorting to efficient digital watermarking systems. This chapter presents a mathematical formulation to define a digital watermarking system and describes the general requirements to be satisfied, with more emphasis given to the aspects of security, robustness, and imperceptibility. After this general discussion, the two main classes of digital watermarking schemes, namely the spread-spectrum watermarking and the side-informed watermarking are explained by highlighting their main advantages and drawbacks. This analysis is completed by the description of a practical implementation of a digital image watermarking scheme. Finally, the use of watermarking systems in the framework of a DRM is deeply analyzed.

scholarly journals Screen-Cam Robust Image Watermarking with Feature-Based Synchronization

2020 ◽  
Vol 10 (21) ◽  
pp. 7494
Author(s):  
Weitong Chen ◽  
Na Ren ◽  
Changqing Zhu ◽  
Qifei Zhou ◽  
Tapio Seppänen ◽  
...  
Keyword(s):  
Image Watermarking ◽  
Gaussian Function ◽  
Geometric Distortion ◽  
Low Pass ◽  
Feature Based ◽  
Robust Image ◽  
Watermarking Scheme ◽  
Watermark Synchronization ◽  
Desynchronization Attacks ◽  
Traditional Image

The screen-cam process, which is taking pictures of the content displayed on a screen with mobile phones or cameras, is one of the main ways that image information is leaked. However, traditional image watermarking methods are not resilient to screen-cam processes with severe distortion. In this paper, a screen-cam robust watermarking scheme with a feature-based synchronization method is proposed. First, the distortions caused by the screen-cam process are investigated. These distortions can be summarized into the five categories of linear distortion, gamma tweaking, geometric distortion, noise attack, and low-pass filtering attack. Then, a local square feature region (LSFR) construction method based on a Gaussian function, modified Harris–Laplace detector, and speeded-up robust feature (SURF) orientation descriptor is developed for watermark synchronization. Next, the message is repeatedly embedded in each selected LSFR by an improved embedding algorithm, which employs a non-rotating embedding method and a preprocessing method, to modulate the discrete Fourier transform (DFT) coefficients. In the process of watermark detection, we fully utilize the captured information and extract the message based on a local statistical feature. Finally, the experimental results are presented to illustrate the effectiveness of the method against common attacks and screen-cam attacks. Compared to the previous schemes, our scheme has not only good robustness against screen-cam attack, but is also effective against screen-cam with additional common desynchronization attacks.

scholarly journals Adaptive Digital Watermarking Scheme Based on Support Vector Machines and Optimized Genetic Algorithm

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Xiaoyi Zhou ◽  
Chunjie Cao ◽  
Jixin Ma ◽  
Longjuan Wang
Keyword(s):  
Genetic Algorithm ◽  
Support Vector Machines ◽  
Digital Watermarking ◽  
Image Watermarking ◽  
Histogram Equalization ◽  
Support Vector ◽  
Digital Products ◽  
Vector Machines ◽  
Low Pass ◽  
Watermarking Scheme

Digital watermarking is an effective solution to the problem of copyright protection, thus maintaining the security of digital products in the network. An improved scheme to increase the robustness of embedded information on the basis of discrete cosine transform (DCT) domain is proposed in this study. The embedding process consisted of two main procedures. Firstly, the embedding intensity with support vector machines (SVMs) was adaptively strengthened by training 1600 image blocks which are of different texture and luminance. Secondly, the embedding position with the optimized genetic algorithm (GA) was selected. To optimize GA, the best individual in the first place of each generation directly went into the next generation, and the best individual in the second position participated in the crossover and the mutation process. The transparency reaches 40.5 when GA’s generation number is 200. A case study was conducted on a 256 × 256 standard Lena image with the proposed method. After various attacks (such as cropping, JPEG compression, Gaussian low-pass filtering (3,0.5), histogram equalization, and contrast increasing (0.5,0.6)) on the watermarked image, the extracted watermark was compared with the original one. Results demonstrate that the watermark can be effectively recovered after these attacks. Even though the algorithm is weak against rotation attacks, it provides high quality in imperceptibility and robustness and hence it is a successful candidate for implementing novel image watermarking scheme meeting real timelines.

Geometrically Invariant Image Watermarking Using Histogram Adjustment

2018 ◽  
Vol 10 (1) ◽  
pp. 54-66
Author(s):  
Zhuoqian Liang ◽  
Bingwen Feng ◽  
Xuba Xu ◽  
Xiaotian Wu ◽  
Tao Yang
Keyword(s):  
Image Processing ◽  
Image Watermarking ◽  
Low Frequency ◽  
Frequency Component ◽  
Geometric Attacks ◽  
Low Pass ◽  
Histogram Bins ◽  
Watermarking Scheme ◽  
Blind Image ◽  
Average Filter

In this article, a blind image watermarking scheme, which is a robust against common image processing and geometric attacks is proposed by adopting the concept of histogram-based embedding. The average filter is employed to low-pass pre-filter the host image. The watermark bits are embedded into the histogram of the low-frequency component and the template bits are embedded in the high-frequency residual. The embedding is performed by adjusting the value of two consecutive histogram bins. Furthermore, a post-quantization is employed after the embedding round to improve robustness. All pixel modifications incurred are based on the human visual system (HVS) characteristics. As a result, a good tradeoff between robustness and imperceptibility is achieved. Experimental results reported the satisfactory performance of the proposed scheme with respect to both common image processing and geometric attacks.

scholarly journals Statistical Assessment of Discrimination Capabilities of a Fractional Calculus Based Image Watermarking System for Gaussian Watermarks

Entropy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 255
Author(s):  
Mario Gonzalez-Lee ◽  
Hector Vazquez-Leal ◽  
Luis J. Morales-Mendoza ◽  
Mariko Nakano-Miyatake ◽  
Hector Perez-Meana ◽  
...  
Keyword(s):  
Fractional Calculus ◽  
Roc Curve ◽  
Gaussian Noise ◽  
False Positive ◽  
Operating Characteristic ◽  
Image Watermarking ◽  
Area Under The Curve ◽  
Statistical Assessment ◽  
Watermarking Scheme ◽  
Fractional Equation

In this paper, we explore the advantages of a fractional calculus based watermarking system for detecting Gaussian watermarks. To reach this goal, we selected a typical watermarking scheme and replaced the detection equation set by another set of equations derived from fractional calculus principles; then, we carried out a statistical assessment of the performance of both schemes by analyzing the Receiver Operating Characteristic (ROC) curve and the False Positive Percentage (FPP) when they are used to detect Gaussian watermarks. The results show that the ROC of a fractional equation based scheme has 48.3% more Area Under the Curve (AUC) and a False Positives Percentage median of 0.2% whilst the selected typical watermarking scheme has 3%. In addition, the experimental results suggest that the target applications of fractional schemes for detecting Gaussian watermarks are as a semi-fragile image watermarking systems robust to Gaussian noise.

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