Fast watermarking of MPEG-1/2 streams using compressed-domain perceptual embedding and a generalized correlator detector

A novel technique is proposed for watermarking of MPEG-1 and MPEG-2 compressed video streams. The proposed scheme is applied directly in the domain of MPEG-1 system streams and MPEG-2 program streams (multiplexed streams). Perceptual models are used during the embedding process in order to avoid degradation of the video quality. The watermark is detected without the use of the original video sequence. A modified correlation-based detector is introduced that applies nonlinear preprocessing before correlation. Experimental evaluation demonstrates that the proposed scheme is able to withstand several common attacks. The resulting watermarking system is very fast and therefore suitable for copyright protection of compressed video

Image watermarking based on the space/spatial-frequency analysis and Hermite functions expansion

International audienceAn image watermarking scheme that combines Hermite functions expansion and space/spatial-frequency analysis is proposed. In the first step, the Hermite functions expansion is employed to select busy regions for watermark embedding. In the second step, the space/spatial-frequency representation and Hermite functions expansion are combined to design the imperceptible watermark, using the host local frequency content. The Hermite expansion has been done by using the fast Hermite projection method. Recursive realization of Hermite functions significantly speeds up the algorithms for regions selection and watermark design. The watermark detection is performed within the space/spatial-frequency domain. The detection performance is increased due to the high information redundancy in that domain in comparison with the space or frequency domains, respectively. The performance of the proposed procedure has been tested experimentally for different watermark strengths, i.e., for different values of the peak signal-to-noise ratio (PSNR). The proposed approach provides high detection performance even for high PSNR values. It offers a good compromise between detection performance (including the robustness to a wide variety of common attacks) and imperceptibility

An Image Forensic Scheme with Robust and Fragile Watermarking for Business Documents

This paper proposes an image forensic scheme with both robust and fragile watermarking techniques for business documents. Through a dual watermarking approach, the proposed scheme can achieve image forensics objectives of (a) identification of source; (b) authentication of documents; and (c) locating the tempered areas of documents due to attacks. An example is presented to prove the concepts of the proposed scheme. Keywords: Image Forensics, Fragile and Robust Watermarking, Business Document

Integrasi Discrete Wavelet Transform dan Singular Value Decomposition pada Watermarking Citra untuk Perlindungan Hak Cipta

Tren masalah watermarking pada sekarang ini adalah bagaimana mengoptimalkan trade-off antara imperceptibility (visibilitas) citra ter-watermark terhadap pengaruh distorsi dan robustness terhadap penyisipan watermark. Masalah menggunakan kekuatan penyisipan berdasarkan Single Scaling Factor (SSF) atau Multiple Scaling Factor (MSF) juga ditemukan. Penelitian ini mengusulkan metode penyisipan watermark untuk perlindungan hak cipta pada citra dan algoritma ekstraksi citra ter-watermark yang dioptimalkan dengan penggabungan Discrete Wavelet Transform (DWT) dan Singular Value Decomposition (SVD). Nilai-nilai singular dari LL3 koefisien sub-band dari citra host dimodifikasi menggunakan nilai tunggal citra watermark biner menggunakan MSFs. Kontribusi utama dari skema yang diusulkan adalah aplikasi DWT-SVD untuk mengidentifikasi beberapa faktor skala yang optimal. Hasil penelitian menunjukkan bahwa skema yang diusulkan menghasilkan nilai Peak Signal to Noise Ratio (PSNR) yang tinggi, yang menunjukkan bahwa kualitas visual gambar yang baik pada masalah citra watermarking telah mengoptimalkan trade-off. Trade-off antara imperceptibility (visibilitas) citra ter-watermark terhadap pengaruh distorsi dan robustness citra ter-watermark terhadap operasi pengolahan citra. Nilai PSNR yang didapat pada citra yang diujikan: baboon=53,184; boat=53,328; cameraman=53,700; lena=53,668; man=53,328; dan pepper sebesar 52,662. Delapan perlakuan khusus pada hasil citra ter-watermark diujikan dan diekstraksi kembali yaitu JPEG 5%, Noise 5%, Gaussian filter 3x3, Sharpening, Histogram Equalization, Scaling 512-256, Gray Quantitation 1bit, dan Cropping 1/8. Hasil dari perlakuan khusus kemudian diukur nilai Normalized Cross-Correlation (NC) yang menghasilkan rata-rata semua citra diperoleh sebesar 0,999 dari satu. Hasil penelitian dari metode yang diusulkan lebih unggul nilai PSNR dan NC dari penelitian sebelumnya. Jadi dapat disimpulkan bahwa penerapan dengan metode DWT-SVD ini mampu menghasilkan citra yang robust namun memiliki tingkat imperceptibility yang cukup tinggi

A constructive and unifying framework for zero-bit watermarking

In the watermark detection scenario, also known as zero-bit watermarking, a watermark, carrying no hidden message, is inserted in content. The watermark detector checks for the presence of this particular weak signal in content. The article looks at this problem from a classical detection theory point of view, but with side information enabled at the embedding side. This means that the watermark signal is a function of the host content. Our study is twofold. The first step is to design the best embedding function for a given detection function, and the best detection function for a given embedding function. This yields two conditions, which are mixed into one `fundamental' partial differential equation. It appears that many famous watermarking schemes are indeed solution to this `fundamental' equation. This study thus gives birth to a constructive framework unifying solutions, so far perceived as very different.Comment: submitted to IEEE Trans. on Information Forensics and Securit

A Comparative Study of Chaotic and White Noise Signals in Digital Watermarking

Digital Watermarking is an ever increasing and important discipline, especially in the modern electronically-driven world. Watermarking aims to embed a piece of information into digital documents which their owner can use to prove that the document is theirs, at a later stage. In this paper, performance analysis of watermarking schemes is performed on white noise sequences and chaotic sequences for the purpose of watermark generation. Pseudorandom sequences are compared with chaotic sequences generated from chaotic skew tent map. In particular, analysis is performed on highpass signals generated from both these watermark generation schemes, along with analysis on lowpass watermarks and white noise watermarks. This analysis focuses on the watermarked images after they have been subjected to common image distortion attacks. It is shown that signals generated from highpass chaotic signals have superior performance than highpass noise signals, in the presence of such attacks. It is also shown that watermarks generated from lowpass chaotic signals have superior performance over the other signal types analysed

Wavelet Domain Watermark Detection and Extraction using the Vector-based Hidden Markov Model

Multimedia data piracy is a growing problem in view of the ease and simplicity provided by the internet in transmitting and receiving such data. A possible solution to preclude unauthorized duplication or distribution of digital data is watermarking. Watermarking is an identifiable piece of information that provides security against multimedia piracy. This thesis is concerned with the investigation of various image watermarking schemes in the wavelet domain using the statistical properties of the wavelet coefficients. The wavelet subband coefficients of natural images have significantly non-Gaussian and heavy-tailed features that are best described by heavy-tailed distributions. Moreover the wavelet coefficients of images have strong inter-scale and inter-orientation dependencies. In view of this, the vector-based hidden Markov model is found to be best suited to characterize the wavelet coefficients. In this thesis, this model is used to develop new digital image watermarking schemes. Additive and multiplicative watermarking schemes in the wavelet domain are developed in order to provide improved detection and extraction of the watermark. Blind watermark detectors using log-likelihood ratio test, and watermark decoders using the maximum likelihood criterion to blindly extract the embedded watermark bits from the observation data are designed. Extensive experiments are conducted throughout this thesis using a number of databases selected from a wide variety of natural images. Simulation results are presented to demonstrate the effectiveness of the proposed image watermarking scheme and their superiority over some of the state-of-the-art techniques. It is shown that in view of the use of the hidden Markov model characterize the distributions of the wavelet coefficients of images, the proposed watermarking algorithms result in higher detection and decoding rates both before and after subjecting the watermarked image to various kinds of attacks

Digital watermarking and novel security devices

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Probabilistic modeling of wavelet coefficients for processing of image and video signals

Statistical estimation and detection techniques are widely used in signal processing including wavelet-based image and video processing. The probability density function (PDF) of the wavelet coefficients of image and video signals plays a key role in the development of techniques for such a processing. Due to the fixed number of parameters, the conventional PDFs for the estimators and detectors usually ignore higher-order moments. Consequently, estimators and detectors designed using such PDFs do not provide a satisfactory performance. This thesis is concerned with first developing a probabilistic model that is capable of incorporating an appropriate number of parameters that depend on higher-order moments of the wavelet coefficients. This model is then used as the prior to propose certain estimation and detection techniques for denoising and watermarking of image and video signals. Towards developing the probabilistic model, the Gauss-Hermite series expansion is chosen, since the wavelet coefficients have non-compact support and their empirical density function shows a resemblance to the standard Gaussian function. A modification is introduced in the series expansion so that only a finite number of terms can be used for modeling the wavelet coefficients with rendering the resulting PDF to become negative. The parameters of the resulting PDF, called the modified Gauss-Hermite (NIGH) PDF, are evaluated in terms of the higher-order sample-moments. It is shown that the MGH PDF fits the empirical density function better than the existing PDFs that use a limited number of parameters do. The proposed MGH PDF is used as the prior of image and video signals in designing maximum a posteriori and minimum mean squared error-based estimators for denoising of image and video signals and log-likelihood ratio-based detector for watermarking of image signals. The performance of the estimation and detection techniques are then evaluated in terms of the commonly used metrics. It is shown through extensive experimentations that the estimation and detection techniques developed utilizing the proposed MGH PDF perform substantially better than those that utilize the conventional PDFs. These results confirm that the superior fit of the MGH PDF to the empirical density function resulting from the flexibility of the MGH PDF in choosing the number of parameters, which are functions of higher-order moments of data, leads to the better performance. Thus, the proposed MGH PDF should play a significant role in wavelet-based image and video signal processin