L’analyse de texture est une composante du traitement d’image qui suscite beaucoup d’intérêt tant les applications qu’elle recouvre sont diverses. En imagerie médicale, les signaux enregistrés sous forme d’images telles que les radiographies de l’os ou les mammographies, présentent une micro-architecture fortement irrégulière qui invite à considérer la formation de ces textures comme la réalisation d’un champ aléatoire. Suite aux travaux précurseurs de Benoit Mandelbrot, de nombreux modèles dérivés du champ brownien fractionnaire ont été proposés pour caractériser l’aspect fractal des images et synthétiser des textures à rugosité prescrite. Ainsi l’estimation des paramètres de ces modèles, a notamment permis de relier la dimension fractale des images à la détection de modifications de la structure osseuse telle qu’on l’observe en cas d’ostéoporose. Plus récemment, d’autres modèles de champs aléatoires, dits anisotropes, ont été utilisés pour décrire des phénomènes présentant des directions privilégiées, et détecter par exemple des anomalies dans les tissus mammaires.Cette thèse porte sur l’élaboration de nouveaux modèles de champs anisotropes, permettant de contrôler localement l’anisotropie des textures. Une première contribution a consisté à définir un champ brownien fractionnaire anisotrope généralisé (GAFBF), et un second modèle basé sur une déformation de champs élémentaires (WAFBF), permettant tous deux de prescrire l’orientation locale de la texture. L’étude de la structure locale de ces champs est menée à l’aide du formalisme des champs tangents. Des procédures de simulation sont mises en oeuvres pour en observer concrètement le comportement, et servir de benchmark à la validation d’outils de détection de l’anisotropie. En effet l’étude de l’orientation locale et de l’anisotropie dans le cadre des textures soulève encore de nombreux problèmes mathématiques, à commencer par la définition rigoureuse de cette orientation. Notre seconde contribution s’inscrit dans cette perspective. En transposant les méthodes de détection de l’orientation basées sur la transformée en ondelettes monogéniques, nous avons été en mesure, pour une vaste classe de champs aléatoires, de définir une notion d’orientation intrinsèque. En particulier l’étude des deux nouveaux modèles de champs anisotropes introduits précédemment, a permis de relier formellement cette notion d’orientation aux paramètres d’anisotropie de ces modèles. Des connexions avec les statistiques directionnelles sont également établies, de façon à caractériser la loi de probabilité des estimateurs d’orientation.Enfin une troisième partie de la thèse est consacrée au problème de la détection de lignes dans les images. Le modèle sous jacent est celui d’une superposition de lignes diffractées (c-a-d convoluées par un noyau de flou) et bruitées, dont il s’agit de retrouver les paramètres de position et d’intensité avec une précision sub-pixel. Nous avons développé dans cet objectif une méthode basée sur le paradigme de la super-résolution. La reformulation du problème en termes d’atomes 1-D a permis de dégager un problème d’optimisation sous contraintes, et de reconstruire ces lignes en atteignant cette précision. Les algorithmes employés pour effectuer la minimisation appartiennent à la famille des algorithmes dits proximaux. La formalisation de ce problème inverse et sa résolution, constituent une preuve de concept ouvrant des perspectives à l’élaboration d’une transformée de Hough revisitée pour la détection ‘continue’ de lignes dans les images. / Texture analysis is a component of image processing which hold the interest in the various applications it covers. In medical imaging, the images recorded such as bone X-rays or mammograms show a highly irregular micro-architecture, which invites to consider these textures formation as a realization of a random field. Following Benoit Mandelbrot’s pioneer work, many models derived from the fractional Brownian field have been proposed to characterize the fractal behavior of images and to synthesize textures with prescribed roughness. Thus, the parameters estimation of these models has made possible to link the fractal dimension of these images to the detection of bone structure alteration as it is observed in the case of osteoporosis. More recently, other models known as anisotropic random fields have been used to describe phenomena with preferred directions, for example for detecting abnormalities in the mammary tissues.This thesis deals with the development of new models of anisotropic fields, allowing to locally control the anisotropy of the textures. A first contribution was to define a generalized anisotropic fractional Brownian field (GAFBF), and a second model based on an elementary field deformation (WAFBF), both allowing to prescribe the local orientation of the texture. The study of the local structure of these fields is carried out using the tangent fields formalism. Simulation procedures are implemented to concretely observe the behavior, and serve as a benchmark for the validation of anisotropy detection tools. Indeed, the investigation of local orientation and anisotropy in the context of textures still raises many mathematical problems, starting with the rigorous definition of this orientation. Our second contribution is in this perspective. By transposing the orientation detection methods based on the monogenic wavelet transform, we have been able, for a wide class of random fields, to define an intrinsic notion of orientation. In particular, the study of the two new models of anisotropic fields introduced previously allowed to formally link this notion of orientation with the anisotropy parameters of these models. Connections with directional statistics are also established, in order to characterize the probability distribution of orientation estimators.Finally, a third part of this thesis was devoted to the problem of the lines detection in images. The underlying model is that of a superposition of diffracted lines (i.e, convoluted by a blur kernel) with presence of noise, whose position and intensity parameters must be recovered with sub-pixel precision. We have developed a method based on the super-resolution paradigm. The reformulation of the problem in the framework of 1-D atoms lead to an optimization problem under constraints, and enables to reconstruct these lines by reaching this precision. The algorithms used to perform the minimization belong to the family of algorithms known as proximal algorithms. The modelization and the resolution of this inverse problem, provides a proof of concept opening perspectives to the development of a revised Hough transform for the continuous detection of lines in images.

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This thesis focuses on the effects of slip-slip, slip-twin, and slip-precipitates interactions on strain hardening, with the intent of developing comprehensive modelling capabilities enabling to investigate unit processes and their collective effects up to the macroscopic response. To this end, the modelling strategy adopted in this work relies on a two-way exchange of information between predictions obtained by discrete dislocation dynamics (DDD) simulations and crystal plasticity laws informed by DDD. At the scale of lattice defects, a DDD tool enabling simulations on any crystalline structure is developed to model dislocation-dislocation, dislocation-twin and dislocation-particles interactions. The tool is first used to quantify the collective effect and strength of dislocation-dislocation interactions on latent-hardening, especially in the case of pure Mg. With regards to slip-twin interactions, a transmission mechanism is implemented in the DDD framework so as to investigate the collective effects of dislocation transmission across a twin-boundary. With respect to slip-particles interactions, an efficient novel DDD approach based on a Fast Fourier Transform (FFT) technique is developed to include the field fluctuations related to elastic heterogeneities giving rise to image forces on dislocation lines. In addition, the DDD-FFT approach allows for the efficient treatment of anisotropic elasticity, thereby paving the way towards performing DDD simulations in low-symmetry polycrystals. The information extracted from the collective dislocation interactions are then passed to a series of constitutive models, and later used to quantify their effects at the scale of the polycrystal. For such purpose, a constitutive framework capable of receiving information from lower scales and establishing a direct connection with DDD simulations is notably developed.

Interest into the effects of weak static magnetic fields on chemical reactions involving spin correlated radical pairs has increased over the last few decades, particularly as scientists have become more curious about the mechanisms by which animals can sense and respond to small variations in the Earth's weak (50 µT) magnetic field. The magnetosensitivity of radical pairs, as dictated by the radical pair mechanism, lies at the heart of the most heavily supported hypothesis of this magnetoreception phenomenon. This thesis is concerned with the spectroscopic investigations of isotropic and anisotropic magnetic field effects in fluorescent systems. First of all, an introduction to spin chemistry and magnetoreception is presented. In chapter 3, the effects of weak radiofrequency oscillating fields when applied in combination with weak static fields are explored in isotropic solutions. The validity of the high-field model, typically used to describe spin dynamics in magnetic resonance, is tested and the effects of orientation and field strength on magnetic field effects are discussed in detail. In Chapter 4, a range of exciplex systems are studied by fluorescence methods and their energetics are explored. The factors which determine the formation of an exciplex, i.e. the complex equilibrium between the exciplex and the spin-correlated radical pair,are considered and used to assess the existence and magnitude of MFEs. Radical pair systems investigated, using MARY spectroscopy, with respect to their potential to act as model chemical compasses are introduced in chapter 5. Solid-state media are used to align the exciplex systems to detect any magnetic field direction dependence. Finally, in chapter 6, AMELIA, an experiment which can directly measure the anisotropic magnetic field response of a system, is presented and applied successfully to systems to detect directly the anisotropic field response of a photoexcited anthracene crystal.

Bone age assessment is a method of assigning a level of biological maturity to a child. It is usually performed either by comparing an x-ray of a child's left hand and wrist with an atlas of known bones, or by analysing specific features of bones such as ratios of width to height, or the degree of overlap with other bones. Both methods of assessment are labour intensive and prone to both inter- and intra-observer variability. This is motivation for developing a computerised method of bone age assessment. The majority of research and development on computerised bone age assessment has focussed on analysing the bones of the hand. The wrist bones, especially the carpal bones, have received far less attention and have only been analysed in young children in which there is clear separation of the bones. An argument is presented that the evidence for excluding the carpal bones from computerised bone age assessment is weak and that research is required to identify the role of carpal bones in the computerised assessment of bone age for children over eight years of age. Computerised analysis of the carpal bones in older children is a difficult computer vision problem plagued by radiographic noise, poor image contrast, and especially poor definition of bone contours. Traditional image processing methods such as region growing fail and even the very successful Canny linear edge detector can only find the simplest of bone edges in these images. The field of partial differential equation-based image processing provides some possible solutions to this problem, such as the use of active contour models to impose constraints upon the contour continuity. However, many of these methods require regularisation to achieve unique and stable solutions. An important part of this regularisation is image denoising. Image denoising was approached through development of a noise model for the Kodak computed radiography system, estimation of noise parameters using a robust estimator of noise per pixel intensity bin, and incorporation of the noise model into a denoising method based on oriented Laplacians. The results for this approach only showed a marginal improvement when using the signal-dependent noise model, although this likely reflects how the noise characteristics were incorporated into the anisotropic diffusion method, rather than the principle of this approach. Even without the signal-dependent noise term the oriented Laplacians denoising of the hand-wrist radiographs was very effective at removing noise and preserving edges.

Nonwoven materials are engineered fabrics, produced by bonding constituent fibres together by mechanical, thermal or chemical means. Such a technology has a great potential to produce material for specific purposes. It is therefore crucial to develop right products with requested properties. This requires a good understanding of the macro and micro behaviours of nonwoven products. In last 40 years, many efforts have been made by researchers to understand the performance of nonwoven materials. One of the main research challenges on the way to this understanding is to link the properties of fibres and the fabric's random fibrous microstructure to the mechanisms of overall material's deformation. The purpose of this research is to study experimentally and numerically the deformation mechanisms of a low-density thermally bonded nonwoven fabric (fibre: Polypropylene; density: 20 gsm). The study started with tensile experiments for the nonwoven material. Specimens with varying dimensions and shapes were tested to investigate the size-dependent deformation mechanisms of the material. Based on obtained results, representative dimensions for the material are determined and used in other experimental and numerical studies. Then standard tensile tests were performed coupled with image analysis. Analysis of the obtained results, allowed the tensile behaviour of the nonwoven material to be determined, the initial study of the effects of material's nonuniform microstructure was also implemented. Based on the experimental results obtained from tensile tests, continuous finite-element models were developed to simulate the material properties of the nonwoven material for its two principle directions: machine direction (MD) and cross direction (CD). Due to the continuous nature of the models, they were only used to establish the mechanical behaviour of the material by treating it as a two-component composite. The effects of bond points, which are a stiffer component within the material, were analysed. Due to the limitations of the continuous FE models, experimental studies were performed focused on the material s microstructure. The latter was detected using an x-ray Micro CT system and an ARAMIS optical strain analysis system. According to the obtained images, the nonwoven fabric is a three-component material. The effects of material's microstructure on stress/strain distributions in the deformed material were studied using advanced image analysis techniques. Based on the experimental results, a new stress calculation method was suggested to substitute the traditional approach, which is not suitable for the analysis of the low density nonwoven material. Then, the fibres orientation distribution and material properties of single fibres were measured due to their significant effects on overall mechanical properties. Finally, discontinuous finite-element models were developed accounting for on the material's three-component structure. The models emphasised the effects of the nonuniform and discontinuous microstructure of the material. Mechanical properties of fibres, the density of fibrous network, the fibres orientation distribution and the arrangement of bond points were used as input parameters for the models, representing features of the material's microstructure. With the use of the developed discontinuous models, the effects of material's microstructure on deformation mechanisms of the low-density nonwoven material were analysed.

The estimation of anisotropic parameters in the shallow subsurface becomes increasingly important for 4C seismic data processing in order to obtain accurate images in both time and depth domain. I focus on two approaches to evaluate anisotropy in seismic data: using P-wave data and PS-converted (C-wave) data. To gain better insight into the accuracy and sensitivity of anisotropic parameters to for instance layering and compaction gradients, I undertake numerical modelling studies and verify the results with full-wave modelling as well as findings from the real data from a 4C data set from the Alba field. The focus of this thesis is on vertical transverse isotropy (VTI) which widely occurs in marine sediments and cannot be neglected in seismic processing. P-wave data alone cannot constrain the vertical velocity and the depth scale of the earth model for a VTI medium. Therefore, the joint inversion of non-hyperbolic P- and converted wave (C-wave) or S-wave data from long offsets has been suggested. I carried out a detailed analysis of the resolution and accuracy of non-hyperbolic moveout inversion for P-, S- and C-waves for a single VTI layer in two parts. First, I introduce the concept of the inherited error delta inh as a measure of the possible resolution of the moveout approximations for the different wave types. The range of this error stays constant regardless of the magnitude of the anisotropic parameter for each wave type. Second, I analyse the accuracy of non-hyperbolic moveout inversion. I find that for anisotropy parameter eta the error of estimation from C-wave data is in most cases about half that from P-wave data. Inversion of non-hyperbolic S-wave moveout data does not resolve the anisotropy parameter due to the presence of cusps in the data. The study is then extended to a multilayered medium considering only P- and C-waves. The results confirm the findings from the single layer case. Furthermore, I investigate phase effects on parameter estimation for P- and C-waves. It is suggested that eta estimated from C-wave data gives a better description of the anisotropy found in a medium than the eta values picked from P-wave data. To verify the above findings near-surface effects are studied on the 4C data from the Alba field and accompanied by a full-waveform modelling study. I find that the picked eta values from P-wave data are distinctly larger than the eta values from C-wave data and also larger than the eta values from VSP data. The full-wave modelling study shows that picked eta values from P-wave data may account for influence of structure such as velocity gradients in the near-surface and are influenced by high velocity ratios and phase reversals. Finally, I have carried out an integrated analysis of the Alba 4C data to demonstrate how seismic anisotropy can be estimated from 4C seismic data and how such information can be used to improve subsurface imaging. The results are presented in two parts. The first part deals with non-hyperbolic moveout analysis for estimating anisotropic parameters to gain improved stacked sections. The second part describes migration model building and final imaging. The models are evaluated by comparison with VSP data results and with a synthetic modelling study for three events of the overburden. The evaluation confirms that the anisotropy parameter obtained from C-wave moveout corresponds better with the VSP data than the values directly estimated from P-wave data.

Displacement Green's function is the building block for some semi-analytical methods like Boundary Element Method (BEM), Distributed Point Source Method (DPCM), etc. In this thesis, the displacement Green`s function in anisotropic media due to a time harmonic point force is studied. Unlike the isotropic media, the Green's function in anisotropic media does not have a closed form solution. The dynamic Green's function for an anisotropic medium can be written as a summation of singular and non-singular or regular parts. The singular part, being similar to the result of static Green's function, is in the form of an integral over an oblique circular path in 3D. This integral can be evaluated either by a numerical integration technique or can be converted to a summation of algebraic terms via the calculus of residue. The other part, which is the regular part, is in the form of an integral over the surface of a unit sphere. This integral needs to be evaluated numerically and its evaluation is considerably more time consuming than the singular part. Obtaining dynamic Green's function and its spatial derivatives involves calculation of these two types of integrals. The spatial derivatives of Green's function are important in calculating quantities like stress and stain tensors. The contribution of this thesis can be divided into two parts. In the first part, different integration techniques including Gauss Quadrature, Simpson's, Chebyshev, and Lebedev integration techniques are tried out and compared for evaluation of dynamic Green’s function. In addition the solution from the residue theorem is included for the singular part. The accuracy and performance of numerical implementation is studied in detail via different numerical examples. Convergence plots are used to analyze the numerical error for both Green's function and its derivatives. The second part of contribution of this thesis relates to the mathematical derivations. As mentioned above, the regular part of dynamic Green's function, being an integral over the surface of a unit sphere, is responsible for the majority of computational time. From symmetry properties, this integration domain can be reduced to a hemisphere, but no more simplification seems to be possible for a general anisotropic medium. In this thesis, the integration domain for regular part is further reduced to a quarter of a sphere for the particular case of transversely isotropic material. This reduction proposed for the first time in this thesis nearly halves the number of integration points for the evaluation of regular part of dynamic Green's function. It significantly reduces the computational time.

This is a report on the fabrication and characterization of anisotropic, porous materials: functionally graded cellular and compositionally anisotropic aerogels. This new class of materials was fabricated by photopolymerization of selected regions of a homogeneous monolith using visible light. Visible light is not significantly absorbed and not significantly scattered by organic molecules and oxide nanoparticles in wet gels and it allows fabrication of deeply penetrating, well-resolved patterns. Simple variations of the exposure geometry allowed fabrication of a wide variety of anisotropic materials without requiring layers or bonding.