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

Embedding distortion analysis in wavelet-domain watermarking

Imperceptibility and robustness are two complementary fundamental requirements of any watermarking algorithm. Low-strength watermarking yields high imperceptibility, but exhibits poor robustness. High-strength watermarking schemes achieve good robustness but often infuse distortions resulting in poor visual quality in host images. This article analyses the embedding distortion for wavelet-based watermarking schemes. We derive the relationship between distortion, measured in mean square error (MSE), and the watermark embedding modification and propose the linear proportionality between MSE and the sum of energy of the selected wavelet coefficients for watermark embedding modification. The initial proposition assumes the orthonormality of discrete wavelet transform. It is further extended for non-orthonormal wavelet kernels using a weighting parameter that follows the energy conservation theorems in wavelet frames. The proposed analysis is verified by experimental results for both non-blind and blind watermarking schemes. Such a model is useful to find the optimum input parameters, including the wavelet kernel, coefficient selection, and subband choices for wavelet domain image watermarking

Contribution des filtres LPTV et des techniques d'interpolation au tatouage numérique

Les Changements d'Horloge Périodiques (PCC) et les filtres Linéaires Variant Périodiquement dans le Temps (LPTV) sont utilisés dans le domaine des télécommunications multi-utilisateurs. Dans cette thèse, nous montrons que, dans l'ensemble des techniques de tatouage par étalement de spectre, ils peuvent se substituer à la modulation par code pseudo-aléatoire. Les modules de décodage optimal, de resynchronisation, de pré-annulation des interférences et de quantification de la transformée d'étalement s'appliquent également aux PCC et aux filtres LPTV. Pour le modèle de signaux stationnaires blancs gaussiens, ces techniques présentent des performances identiques à l'étalement à Séquence Directe (DS) classique. Cependant, nous montrons que, dans le cas d'un signal corrélé localement, la luminance d'une image naturelle notamment, la périodicité des PCC et des filtres LPTV associée à un parcours d'image de type Peano-Hilbert conduit à de meilleures performances. Les filtres LPTV sont en outre un outil plus puissant qu'une simple modulation DS. Nous les utilisons pour effectuer un masquage spectral simultanément à l'étalement, ainsi qu'un rejet des interférences de l'image dans le domaine spectral. Cette dernière technique possède de très bonnes performances au décodage. Le second axe de cette thèse est l'étude des liens entre interpolation et tatouage numérique. Nous soulignons d'abord le rôle de l'interpolation dans les attaques sur la robustesse du tatouage. Nous construisons ensuite des techniques de tatouage bénéficiant des propriétés perceptuelles de l'interpolation. La première consiste en des masques perceptuels utilisant le bruit d'interpolation. Dans la seconde, un schéma de tatouage informé est construit autour de l'interpolation. Cet algorithme, qu'on peut relier aux techniques de catégorisation aléatoire, utilise des règles d'insertion et de décodage originales, incluant un masquage perceptuel intrinsèque. Outre ces bonnes propriétés perceptuelles, il présente un rejet des interférences de l'hôte et une robustesse à diverses attaques telles que les transformations valumétriques. Son niveau de sécurité est évalué à l'aide d'algorithmes d'attaque pratiques. ABSTRACT : Periodic Clock Changes (PCC) and Linear Periodically Time Varying (LPTV) filters have previously been applied to multi-user telecommunications in the Signal and Communications group of IRIT laboratory. In this thesis, we show that in each digital watermarking scheme involving spread-spectrum, they can be substituted to modulation by a pseudo-noise. The additional steps of optimal decoding, resynchronization, pre-cancellation of interference and quantization of a spread transform apply also to PCCs and LPTV filters. For white Gaussian stationary signals, these techniques offer similar performance as classical Direct Sequence (DS) spreading. However we show that, in the case of locally correlated signals such as image luminance, the periodicity of PCCs and LPTV filters associated to a Peano-Hilbert scan leads to better performance. Moreover, LPTV filters are a more powerful tool than simple DS modulation. We use LPTV filters to conduct spectrum masking simultaneous to spreading, as well as image interference cancellation in the spectral domain. The latter technique offers good decoding performance. The second axis of this thesis is the study of the links between interpolation and digital watermarking.We stress the role of interpolation in attacks on the watermark.We propose then watermarking techniques that benefit from interpolation perceptual properties. The first technique consists in constructing perceptualmasks proportional to an interpolation error. In the second technique, an informed watermarking scheme derives form interpolation. This scheme exhibits good perceptual properties, host-interference rejection and robustness to various attacks such as valumetric transforms. Its security level is assessed by ad hoc practical attack algorithms