Deformable image registration (DIR) is a type of registration that calculates a deformable vector field (DVF) between two image data sets and permits contour and dose propagation. However the calculation of a DVF is considered an ill-posed problem, as there is no exact solution to a deformation problem, therefore all DVFs calculated contain errors. As a result it is important to evaluate and assess the accuracy and limitations of any DIR algorithm intended for clinical use. The influence of image quality on the DIR algorithms performance was also evaluated. The hybrid DIR algorithm in RayStation 4.0.1.4 was assessed using a number of evaluation methods and data. The evaluation methods were point of interest (POI) propagation, contour propagation and dose measurements. The data types used were phantom and patient data. A number of metrics were used for quantitative analysis and visual inspection was used for qualitative analysis. The quantitative and qualitative results indicated that all DVFs calculated by the DIR algorithm contained errors which translated into errors in the propagated contours and propagated dose. The results showed that the errors were largest for small contour volumes (<20cm3) and for large anatomical volume changes between the image sets, which pushes the algorithms ability to deform, a significant decrease in accuracy was observed for anatomical volume changes of greater than 10%. When the propagated contours in the head and neck were used for planning the errors in the DVF were found to cause under dosing to the target tumour by up to 32% and over dosing to the organs at risk (OAR) by up to 12% which is clinically significant. The results also indicated that the image quality does not have a significant effect on the DIR algorithms calculations. Dose measurements indicated errors in the DVF calculations that could potentially be clinically significant. The results indicate that contour propagation and dose propagation must be used with caution if clinical use is intended. For clinical use contour propagation requires evaluation of every propagated contour by an expert user and dose propagation requires thorough evaluation of the DVF.

In scientific computing, it is very common to visualize the approximate solution obtained by a numerical PDE solver by drawing surface or contour plots of all or some components of the associated approximate solutions. These plots are used to investigate the behavior of the solution and to display important properties or characteristics of the approximate solutions. In this thesis, we consider techniques for drawing such contour plots for the solution of two and three dimensional PDEs. We first present three fast contouring algorithms in two dimensions over an underlying unstructured mesh. Unlike standard contouring algorithms, our algorithms do not require a fine structured approximation. We assume that the underlying PDE solver generates approximations at some scattered data points in the domain of interest. We then generate a piecewise cubic polynomial interpolant (PCI) which approximates the solution of a PDE at off-mesh points based on the DEI (Differential Equation Interpolant) approach. The DEI approach assumes that accurate approximations to the solution and first-order derivatives exist at a set of discrete mesh points. The extra information required to uniquely define the associated piecewise polynomial is determined based on almost satisfying the PDE at a set of collocation points. In the process of generating contour plots, the PCI is used whenever we need an accurate approximation at a point inside the domain. The direct extension of the both DEI-based interpolant and the contouring algorithm to three dimensions is also investigated. The use of the DEI-based interpolant we introduce for visualization can also be used to develop effective Adaptive Mesh Refinement (AMR) techniques and global error estimates. In particular, we introduce and investigate four AMR techniques along with a hybrid mesh refinement technique. Our interest is in investigating how well such a `generic' mesh selection strategy, based on properties of the problem alone, can perform compared with a special-purpose strategy that is designed for a specific PDE method. We also introduce an \`{a} posteriori global error estimator by introducing the solution of a companion PDE defined in terms of the associated PCI.

In scientific computing, it is very common to visualize the approximate solution obtained by a numerical PDE solver by drawing surface or contour plots of all or some components of the associated approximate solutions. These plots are used to investigate the behavior of the solution and to display important properties or characteristics of the approximate solutions. In this thesis, we consider techniques for drawing such contour plots for the solution of two and three dimensional PDEs. We first present three fast contouring algorithms in two dimensions over an underlying unstructured mesh. Unlike standard contouring algorithms, our algorithms do not require a fine structured approximation. We assume that the underlying PDE solver generates approximations at some scattered data points in the domain of interest. We then generate a piecewise cubic polynomial interpolant (PCI) which approximates the solution of a PDE at off-mesh points based on the DEI (Differential Equation Interpolant) approach. The DEI approach assumes that accurate approximations to the solution and first-order derivatives exist at a set of discrete mesh points. The extra information required to uniquely define the associated piecewise polynomial is determined based on almost satisfying the PDE at a set of collocation points. In the process of generating contour plots, the PCI is used whenever we need an accurate approximation at a point inside the domain. The direct extension of the both DEI-based interpolant and the contouring algorithm to three dimensions is also investigated. The use of the DEI-based interpolant we introduce for visualization can also be used to develop effective Adaptive Mesh Refinement (AMR) techniques and global error estimates. In particular, we introduce and investigate four AMR techniques along with a hybrid mesh refinement technique. Our interest is in investigating how well such a `generic' mesh selection strategy, based on properties of the problem alone, can perform compared with a special-purpose strategy that is designed for a specific PDE method. We also introduce an \`{a} posteriori global error estimator by introducing the solution of a companion PDE defined in terms of the associated PCI.

Orientador: Aluir Porfírio Dal Poz / Banca: Nilton Nobuhiro Imai / Banca: Maurício Galo / Banca: Edson Aparecido Mitishita / Resumo: As metodologias para a extração automática de telhados desempenham um papel importante no contexto de aquisição de informação espacial para Sistemas de Informação Geográficas (SIG). Neste sentido, este trabalho propõe uma metodologia para extração automática de contornos de telhado de edifícios utilizando dados de varredura a laser. A metodologia baseiase em duas etapas principais: 1) Extração de regiões altas (edifícios, árvores etc.) de um Modelo Digital de Elevação (MDE) gerado a partir dos dados laser; 2) Extração das regiões altas que correspondem a contornos de telhados. Na primeira etapa são utilizadas as técnicas de divisão recursiva, via estrutura quadtree e de fusão Bayesiana de regiões considerando Markov Random Field (MRF). Inicialmente a técnica de divisão recursiva é usada para particionar o MDE em regiões homogêneas. No entanto, devido a ligeiras diferenças de altura no MDE, nesta etapa a fragmentação das regiões pode ser relativamente alta. Para minimizar essa fragmentação, a técnica de fusão Bayesiana de regiões é aplicada nos dados segmentados. Utiliza-se para tanto um modelo hierárquico, cujas alturas médias das regiões dependem de uma média geral e de um efeito aleatório, que incorpora a relação de vizinhança entre elas. A distribuição a priori para o efeito aleatório é especificada como um modelo condicional auto-regressivo (CAR). As distribuições a posteriori para os parâmetros de interesse foram obtidas utilizando o Amostrador de Gibbs. Na segunda etapa os contornos de telhados são identificados entre todos os objetos altos extraídos na etapa anterior. Levando em conta algumas propriedades de telhados e as medidas de alguns atributos (por exemplo, área, retangularidade, ângulos entre eixos principais de objetos) é construída uma função de energia a partir do modelo MRF. / Abstract: Methodologies for automatic building roof extraction are important in the context of spatial information acquisition for geographical information systems (GIS). Thus, this work proposes a methodology for automatic extraction of building roof contour from laser scanning data. The methodology is based on two stages: 1) Extraction of high regions (buildings, trees etc.) from a Digital Elevation Model (DEM) derived from laser scanning data; 2) Building roof contour extraction. In the first stage is applied the recursive splitting technique using the quadtree structure followed by a Bayesian merging technique considering Markov Random Field (MRF) model. The recursive splitting technique subdivides the DEM into homogeneous regions. However, due to slight height differences in the DEM, in this stage the region fragmentation can be relatively high. In order to minimize the fragmentation, a region merging technique based on the Bayesian framework is applied to the previously segmented data. Thus, a hierarchical model is proposed, whose height values in the data depend on a general mean plus a random effect. The prior distribution for the random effects is specified by the Conditional Autoregressive (CAR) model. The posterior probability distributions are obtained by the Gibbs sampler. In the second stage the building roof contours are identified among all high objects extracted previously. / Doutor

Dans cette thèse, nous nous intéressons au problème de la segmentation de portraits numériques. Nous appelons portrait numérique la photographie d’une personne avec un cadre allant grossièrement du gros plan au plan poitrine. Le problème abordé dans ce travail est un cas spécifique de la segmentation d’images où il s’agit notamment de définir précisément la frontière de la région « cheveux ». Ce problème est par essence très délicat car les attributs de la région « cheveux » (géométrie, couleur, texture) présentent une grande variabilité à la fois entre les personnes et au sein de la région. Notre cadre applicatif est un système d’« essayage virtuel » de lunettes à destination du grand public, il n’est pas possible de contrôler les conditions de prise de vue comme l’éclairage de la scène ou la résolution des images, ce qui accroît encore la diculté du problème. L’approche proposée pour la segmentation de portraits numériques est une approche du plus grossier au plus fin procédant par étapes successives. Nous formulons le problème comme celui d’une segmentation multi-régions, en introduisant comme « régions secondaires », les régions adjacentes à la région « cheveux » , c.-à-d. les régions « peau » et « fond ». La méthode est fondée sur l’apparence (appearance-based method) et a comme spécificité le fait de déterminer les descripteurs de régions les plus adaptés à partir d’une base d’images d’apprentissage et d’outils statistiques. À la première étape de la méthode, nous utilisons l’information contextuelle d’un portrait numérique — connaissances a priori sur les relations spatiales entre régions— pour obtenir des échantillons des régions « cheveux », « peau » et « fond ». L’intérêt d’une approche fondée sur l’apparence est de pouvoir s’adapter à la fois aux conditions de prises de vue ainsi qu’aux attributs de chaque régions. Au cours de cette étape, nous privilégions les modèles de forme polygonaux couplés aux contours actifs pour assurer la robustesse du modèle. Lors de la seconde étape, à partir des échantillons détectés à l’étape précédente, nous introduisons un descripteur prenant en compte l’information de couleur et de texture. Nous proposons une segmentation grossière par classification en nous appuyant à nouveau sur l’information contextuelle : locale d’une part grâce aux champs de Markov, globale d’autre part grâce à un modèle a priori de segmentation obtenu par apprentissage qui permet de rendre les résultats plus robustes. La troisième étape ane les résultats en définissant la frontière des « cheveux » comme une région de transition. Cette dernière contient les pixels dont l’apparence provient du mélange de contributions de deux régions (« cheveux »et « peau » ou «fond »). Ces deux régions de transition sont post-traitées par un algorithme de «démélange » (digital matting) pour estimer les coecients de transparence entre « cheveux » et « peau », et entre « cheveux » et « fond ». À l’issue de ces trois étapes, nous obtenons une segmentation précise d’un portrait numérique en trois « calques », contenant en chaque pixel l’information de transparence entre les régions « cheveux », « peau » et « fond ». Les résultats obtenus sur une base d’images de portraits numériques ont mis en évidence les bonnes performances de notre méthode. / In this thesis, we are interested in the problem of the segmentation of digital portraits. We call digital portrait the photography of a person with a frame roughly ranging from the close-up to the chest plane. The problem addressed in this work is a specific case of the segmentation of images where it is especially necessary to define precisely the border of the "hair" region. This problem is inherently very delicate because the attributes of the "hair" region (geometry, color, texture) present an important variability between people and within the region. Our application is a system of "virtual fitting" of glasses for the general audience, it is not possible to control the shooting conditions such as stage lighting or image resolution, which increases the difficulty of the problem. The approach proposed for the segmentation of digital portraits is an approach « coarse to fine », proceeding in successive stages. We formulate the problem as a multi-region segmentation, introducing as "secondary regions" regions adjacent to the "hair" region, ie, the "skin" and "background" regions. The method is based on appearance-based method and has as a specificity the determination of the descriptors of regions most adapted from a database of learning and statistical tools. In the first step of the method, we use the contextual information of a Digital portrait - a priori knowledge about the spatial relations between regions - to obtain samples of the regions "hair", "skin" and "background". The value of an appearance-based approach is to be able to adapt to both the shooting conditions and the attributes of each region. During this stage, we prefer polygonal shape models coupled with active contours to ensure the robustness of the model. In the second step, from the samples detected in the previous step, we introduce a descriptor taking into account the color and texture information. We propose a rough segmentation by classification by relying on the contextual information: local on the one hand thanks to the Markov fields, global on the other hand thanks to an a priori model of segmentation obtained by learning which il allow to obtain robust results. The third stage refines the results by defining the border of "hair" as a transition region. This région contains the pixels whose appearance comes from the mixture of contributions of two regions ("hair" and "skin" or "background"). These two transition regions are post-processed by a digital matting algorithm to estimate the coefficients of transparency between "hair" and "skin", and between "hair" and "background". At the end of these three steps, we obtain a precise segmentation of a digital portrait into three "layers", containing in each pixel the information of transparency between the regions "hair", "skin" and "background". The results obtained on the basis of images of digital portraits have highlighted the good performance of our method.

La taille de la zone plastique en pointe de fissure dans un matériau est directement liée au facteur d’intensité de contrainte pour une configuration donnée. Cette étude utilise la technique d’indentation avec une très faible charge afin d’étudier la taille de la zone plastique cyclique et monotone au voisinage de la fissure. La zone plastique est caractérisée par la relation entre la dureté, le module réduit, le travail élastique, le travail plastique, l’indice de plasticité et la distance par rapport à la pointe de fissure. Les essais sont menés sur une éprouvette CT pour un alliage d’aluminium 2024T351. Dans une étude complémentaire, le contour des zones plastiques en fond de fissure en mode mixte, le rayon minimum de zone plastique (MPZR) et la direction de la fissure initiale pour l’alliage d’aluminium 2024T351 sur un “Compact Tension spécimen” est déterminé en utilisant le logiciel Matlab. Nous avons calculé la forme, la taille de la zone plastique au fond de fissure, le rayon minimum de la zone plastique par rapport à l’angle de chargement et le facteur d’intensité de contrainte en utilisant le critère de Von Mises. L’étude est effectuée pour les divers angles de chargement. Nous avons constaté que le chargement en mode mixte (13 = 600) est le plus néfaste pour le matériau. / The plastic zone size associated with a propagating crack in a material is directly related to the stress intensity factor for a given configuration. This work utilizes the ultra-low-load indentation techniques to study the cyclic and monotonic plastic zone size at the fatigue crack tip based on the relationship between the hardness, elastic work, plastic work, plasticity index and the distance from the crack tip. The study is conducted essentially on the aluminium alloy 2024T351. In a second part of this work, we study the contour of mixed mode crack-tip plastic zones, the minimum plastic zone radius (MPZR) and the direction of initial crack for the aluminium alloy 2024T351 in a Compact tension specimen by using Matlab software. We have computed the shape, size of plastic zone at crack-tip and the minimum plastic zone radius with respect to the loading angle and stress intensity factor in linear elastic fracture mechanics for plane strain condition according to Von Mises yield criteria, the study is conducted for various loading angle. We found that the mixed mode loading (F36O°) can lead to earlier material fracture earlier than any other biaxial loading.

Made available in DSpace on 2015-03-26T13:45:34Z (GMT). No. of bitstreams: 1 texto completo.pdf: 833570 bytes, checksum: 24fbb8cfc82b6070bc53272b50a6af11 (MD5) Previous issue date: 2011-02-25 / This dissertation is devoted to the study of stable maps from closed orientable surfaces to the sphere. We study graphs as invariants of such maps and according to Hacon, Mendes de Jesus and Romero-Fuster [14], every bipartite graph is realized by a stable map with arbitrary degree. According to Demoto [2], we show that the minimal contour of a stable map f between two spheres has exactly 2deg(f) cusps and no self-intersections. / Esta dissertação é dedicada ao estudo de aplicações estáveis de superfícies fechadas e orientadas na esfera. Vamos estudar grafos como invariantes de tais aplicações estáveis e de acordo com Hacon, Mendes de Jesus e Romero-Fuster [14], todo grafo bipartido é realizado por aplicações estáveis desse tipo, com grau arbitrário. Segundo Demoto [2], vamos mostrar que o contorno minimal de uma aplicação estável f entre duas esferas possui exatamente 2deg(f) cúspides e nenhuma auto-interseção.

Este trabalho apresenta um método para análise do contorno de gotas de chuva artificial em imagem digital, o qual se caracteriza como uma ferramenta para melhor compreensão dos processos agrícolas que envolvem o uso de chuvas artificiais, como a irrigação e a aplicação de defensivos, sendo desenvolvido com o uso de técnicas para análise de formas bidimensionais e processamento de sinais, como representação de formas por contornos paramétricos, análise de Fourier e filtragem gaussiana. Os resultados obtidos demonstram precisão na análise de imagens de aglomerados de gotas, acrescentando as características de descritor apresentadas pela curvatura, assim como a flexibilidade de calibração oferecidas pela abordagem multi-escala adotada, possibilitando a obtenção de erros de medida não maiores que 5%, para os padrões circulares testados com raios entre 10 e 200 pixels / This work presents a method for contour analysis of artificial rain drop based on both digital image and curvature processing. The method is characterized as a tool, which allows a better understanding of the raindrops in irrigation and agrochemicals spraying processes. Its development was based on parametric contours representation of shapes, Fourier analysis, and Gaussian filtering. Results show the suitability of the method, which presents errors smaller than 5% for curvature determination in the range of the radius variation in betwen 10 and 200 pixels as well as the ability for raindrop clusters analysis

L’usinage tient une place considérable dans l’industrie, c’est un des procédés les plus répandu. A ce titre, la maitrise du procédé de fraisage, notamment lors d’une opération de finition, est devenu un enjeu majeur dans le secteur industriel. La compréhension des phénomènes physiques présents lors d’un usinage de finition est un facteur important pour l’optimisation d’un procédé de fabrication par enlèvement de matière.Afin de déterminer les paramètres influents lors d’un usinage de finition, notamment lors d’un fraisage de profil, une nouvelle méthodologie expérimentale sera développée. Ces travaux vont s’articuler autour de trois activités principales :- La mise en place d’une instrumentation capable de recueillir une image des efforts de coupe. Ce dispositif expérimental devra être équipé de capteurs et d’une chaine d’acquisition pour acquérir les composantes des efforts selon les directions x et y.- Le développement d’un nouveau dispositif passe par une étape qualification dans laquelle une série de tests permettra d’établir la capabilité du montage.- Cette étude expérimentale s’accompagne d’une campagne d’essais permettant de définir les paramètres les plus influents lors d’un fraisage de profil de finition. / Machining holds an important place in the industry, this is one the most common process. As thus, mastering the milling process, especially during a finishing operation, has become a major issue in the insdustrial sector. Understanding the physical phenomena present in a finishing machining is an important factor for the optimization of a manufacturing process by removing material.In order to determine the most important factors during a finishing machining, in particular during a profile milling, a new experimental methodology will be developed. This work will focus on three main activities :- The introduction of instrumentation capable of collecting an image cutting forces. This experimental device must be equipped with sensors and an acquisition channel to acquire the components of the forces in the x and y directions.- The development of a new device going through a stage qualification in which a series of tests will establish the capability of experimental device.- This experimental study is accompanied by a series of tests to define the most important parameters in a finishing profile milling

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