ИНТЕЛЛЕКТУАЛЬНЫЙ числовым программным ДЛЯ MIMD-компьютер

For most scientific and engineering problems simulated on computers the solving of problems of the computational mathematics with approximately given initial data constitutes an intermediate or a final stage. Basic problems of the computational mathematics include the investigating and solving of linear algebraic systems, evaluating of eigenvalues and eigenvectors of matrices, the solving of systems of non-linear equations, numerical integration of initial- value problems for systems of ordinary differential equations.Для більшості наукових та інженерних задач моделювання на ЕОМ рішення задач обчислювальної математики з наближено заданими вихідними даними складає проміжний або остаточний етап. Основні проблеми обчислювальної математики відносяться дослідження і рішення лінійних алгебраїчних систем оцінки власних значень і власних векторів матриць, рішення систем нелінійних рівнянь, чисельного інтегрування початково задач для систем звичайних диференціальних рівнянь.Для большинства научных и инженерных задач моделирования на ЭВМ решение задач вычислительной математики с приближенно заданным исходным данным составляет промежуточный или окончательный этап. Основные проблемы вычислительной математики относятся исследования и решения линейных алгебраических систем оценки собственных значений и собственных векторов матриц, решение систем нелинейных уравнений, численного интегрирования начально задач для систем обыкновенных дифференциальных уравнений

Topology-preserving watermarking of vector graphics

Watermarking techniques for vector graphics dislocate vertices in order to embed imperceptible, yet detectable, statistical features into the input data. The embedding process may result in a change of the topology of the input data, e.g., by introducing self-intersections, which is undesirable or even disastrous for many applications. In this paper we present a watermarking framework for two-dimensional vector graphics that employs conventional watermarking techniques but still provides the guarantee that the topology of the input data is preserved. The geometric part of this framework computes so-called maximum perturbation regions (MPR) of vertices. We propose two efficient algorithms to compute MPRs based on Voronoi diagrams and constrained triangulations. Furthermore, we present two algorithms to conditionally correct the watermarked data in order to increase the watermark embedding capacity and still guarantee topological correctness. While we focus on the watermarking of input formed by straight-line segments, one of our approaches can also be extended to circular arcs. We conclude the paper by demonstrating and analyzing the applicability of our framework in conjunction with two well-known watermarking techniques

Information Analysis for Steganography and Steganalysis in 3D Polygonal Meshes

Information hiding, which embeds a watermark/message over a cover signal, has recently found extensive applications in, for example, copyright protection, content authentication and covert communication. It has been widely considered as an appealing technology to complement conventional cryptographic processes in the field of multimedia security by embedding information into the signal being protected. Generally, information hiding can be classified into two categories: steganography and watermarking. While steganography attempts to embed as much information as possible into a cover signal, watermarking tries to emphasize the robustness of the embedded information at the expense of embedding capacity. In contrast to information hiding, steganalysis aims at detecting whether a given medium has hidden message in it, and, if possible, recover that hidden message. It can be used to measure the security performance of information hiding techniques, meaning a steganalysis resistant steganographic/watermarking method should be imperceptible not only to Human Vision Systems (HVS), but also to intelligent analysis. As yet, 3D information hiding and steganalysis has received relatively less attention compared to image information hiding, despite the proliferation of 3D computer graphics models which are fairly promising information carriers. This thesis focuses on this relatively neglected research area and has the following primary objectives: 1) to investigate the trade-off between embedding capacity and distortion by considering the correlation between spatial and normal/curvature noise in triangle meshes; 2) to design satisfactory 3D steganographic algorithms, taking into account this trade-off; 3) to design robust 3D watermarking algorithms; 4) to propose a steganalysis framework for detecting the existence of the hidden information in 3D models and introduce a universal 3D steganalytic method under this framework. %and demonstrate the performance of the proposed steganalysis by testing it against six well-known 3D steganographic/watermarking methods. The thesis is organized as follows. Chapter 1 describes in detail the background relating to information hiding and steganalysis, as well as the research problems this thesis will be studying. Chapter 2 conducts a survey on the previous information hiding techniques for digital images, 3D models and other medium and also on image steganalysis algorithms. Motivated by the observation that the knowledge of the spatial accuracy of the mesh vertices does not easily translate into information related to the accuracy of other visually important mesh attributes such as normals, Chapters 3 and 4 investigate the impact of modifying vertex coordinates of 3D triangle models on the mesh normals. Chapter 3 presents the results of an empirical investigation, whereas Chapter 4 presents the results of a theoretical study. Based on these results, a high-capacity 3D steganographic algorithm capable of controlling embedding distortion is also presented in Chapter 4. In addition to normal information, several mesh interrogation, processing and rendering algorithms make direct or indirect use of curvature information. Motivated by this, Chapter 5 studies the relation between Discrete Gaussian Curvature (DGC) degradation and vertex coordinate modifications. Chapter 6 proposes a robust watermarking algorithm for 3D polygonal models, based on modifying the histogram of the distances from the model vertices to a point in 3D space. That point is determined by applying Principal Component Analysis (PCA) to the cover model. The use of PCA makes the watermarking method robust against common 3D operations, such as rotation, translation and vertex reordering. In addition, Chapter 6 develops a 3D specific steganalytic algorithm to detect the existence of the hidden messages embedded by one well-known watermarking method. By contrast, the focus of Chapter 7 will be on developing a 3D watermarking algorithm that is resistant to mesh editing or deformation attacks that change the global shape of the mesh. By adopting a framework which has been successfully developed for image steganalysis, Chapter 8 designs a 3D steganalysis method to detect the existence of messages hidden in 3D models with existing steganographic and watermarking algorithms. The efficiency of this steganalytic algorithm has been evaluated on five state-of-the-art 3D watermarking/steganographic methods. Moreover, being a universal steganalytic algorithm can be used as a benchmark for measuring the anti-steganalysis performance of other existing and most importantly future watermarking/steganographic algorithms. Chapter 9 concludes this thesis and also suggests some potential directions for future work

Modeling and Simulation in Engineering

The general aim of this book is to present selected chapters of the following types: chapters with more focus on modeling with some necessary simulation details and chapters with less focus on modeling but with more simulation details. This book contains eleven chapters divided into two sections: Modeling in Continuum Mechanics and Modeling in Electronics and Engineering. We hope our book entitled "Modeling and Simulation in Engineering - Selected Problems" will serve as a useful reference to students, scientists, and engineers

Adaptive 3D web-based environment for heterogeneous volume objects.

The Internet was growing fast on the last decade. Interaction and visualisation became an essential feature online. The demand for online modelling and rendering in a real-time, adaptive and interactive manner exceeded the growth and development of the hardware resources including computational power and memories. Building up and accessing an instant 3D Web-based and plugin-free platform started to be a must in order to generate 3D volumes. Modelling and rendering complicated heterogeneous volumes using online applications requires good Internet bandwidth and high computational power. A large number of 3D modelling tools designed to create complicated models in an interactive manner are now available online, the problem of using such tools is that the user needs to acquire a certain level of modelling knowledge In this work, we identify the problem, introduce the theoretical background and discuss the theory about Web-based modelling and rendering, including client- server approach, scenario optimization by solving constraint satisfaction problem, and complexity analysis. We address the challenges of designing, implementing and testing an online, Web-based, instant 3D modelling and rendering environment and we discuss some of its characteristics including adaptivity, platform independence, interactivity, and easy-to-use after presenting the theoretical part of implementing such an environment. We also introduce platform-independent modelling and rendering environment for complicated heterogeneous volumes with colour attributes based on client- server architecture. The work includes analysis and implementation for different rendering approaches suitable for different kind of users. We also discuss the performance of the proposed environment by comparing the rendering approaches. As an additional feature of our modelling system, we discuss aspects of securing the model transferring between client and the server

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

Three Dimensional Nonlinear Statistical Modeling Framework for Morphological Analysis

This dissertation describes a novel three-dimensional (3D) morphometric analysis framework for building statistical shape models and identifying shape differences between populations. This research generalizes the use of anatomical atlases on more complex anatomy as in case of irregular, flat bones, and bones with deformity and irregular bone growth. The foundations for this framework are: 1) Anatomical atlases which allow the creation of homologues anatomical models across populations; 2) Statistical representation for output models in a compact form to capture both local and global shape variation across populations; 3) Shape Analysis using automated 3D landmarking and surface matching. The proposed framework has various applications in clinical, forensic and physical anthropology fields. Extensive research has been published in peer-reviewed image processing, forensic anthropology, physical anthropology, biomedical engineering, and clinical orthopedics conferences and journals. The forthcoming discussion of existing methods for morphometric analysis, including manual and semi-automatic methods, addresses the need for automation of morphometric analysis and statistical atlases. Explanations of these existing methods for the construction of statistical shape models, including benefits and limitations of each method, provide evidence of the necessity for such a novel algorithm. A novel approach was taken to achieve accurate point correspondence in case of irregular and deformed anatomy. This was achieved using a scale space approach to detect prominent scale invariant features. These features were then matched and registered using a novel multi-scale method, utilizing both coordinate data as well as shape descriptors, followed by an overall surface deformation using a new constrained free-form deformation. Applications of output statistical atlases are discussed, including forensic applications for the skull sexing, as well as physical anthropology applications, such as asymmetry in clavicles. Clinical applications in pelvis reconstruction and studying of lumbar kinematics and studying thickness of bone and soft tissue are also discussed

Application of Machine Learning within Visual Content Production

We are living in an era where digital content is being produced at a dazzling pace. The heterogeneity of contents and contexts is so varied that a numerous amount of applications have been created to respond to people and market demands. The visual content production pipeline is the generalisation of the process that allows a content editor to create and evaluate their product, such as a video, an image, a 3D model, etc. Such data is then displayed on one or more devices such as TVs, PC monitors, virtual reality head-mounted displays, tablets, mobiles, or even smartwatches. Content creation can be simple as clicking a button to film a video and then share it into a social network, or complex as managing a dense user interface full of parameters by using keyboard and mouse to generate a realistic 3D model for a VR game. In this second example, such sophistication results in a steep learning curve for beginner-level users. In contrast, expert users regularly need to refine their skills via expensive lessons, time-consuming tutorials, or experience. Thus, user interaction plays an essential role in the diffusion of content creation software, primarily when it is targeted to untrained people. In particular, with the fast spread of virtual reality devices into the consumer market, new opportunities for designing reliable and intuitive interfaces have been created. Such new interactions need to take a step beyond the point and click interaction typical of the 2D desktop environment. The interactions need to be smart, intuitive and reliable, to interpret 3D gestures and therefore, more accurate algorithms are needed to recognise patterns. In recent years, machine learning and in particular deep learning have achieved outstanding results in many branches of computer science, such as computer graphics and human-computer interface, outperforming algorithms that were considered state of the art, however, there are only fleeting efforts to translate this into virtual reality. In this thesis, we seek to apply and take advantage of deep learning models to two different content production pipeline areas embracing the following subjects of interest: advanced methods for user interaction and visual quality assessment. First, we focus on 3D sketching to retrieve models from an extensive database of complex geometries and textures, while the user is immersed in a virtual environment. We explore both 2D and 3D strokes as tools for model retrieval in VR. Therefore, we implement a novel system for improving accuracy in searching for a 3D model. We contribute an efficient method to describe models through 3D sketch via an iterative descriptor generation, focusing both on accuracy and user experience. To evaluate it, we design a user study to compare different interactions for sketch generation. Second, we explore the combination of sketch input and vocal description to correct and fine-tune the search for 3D models in a database containing fine-grained variation. We analyse sketch and speech queries, identifying a way to incorporate both of them into our system's interaction loop. Third, in the context of the visual content production pipeline, we present a detailed study of visual metrics. We propose a novel method for detecting rendering-based artefacts in images. It exploits analogous deep learning algorithms used when extracting features from sketches