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Computed tomography is a very useful technic which allow non-invasive diagnosis in many applications for example is used with success in industry and medicine. However, manual analysis of the interesting structures can be tedious and extremely time consuming, or even impossible due its complexity. Therefore in this thesis we study and develop discrete geometry and topology algorithms suitable for use in many practical applications, especially, in the problem of automatic quantitative analysis of the human airway trees based on computed tomography images. In the first part, we define basic notions used in discrete topology and geometry then we showed that several class of discrete methods like skeletonisation algorithms, medial axes, tunnels closing algorithms and tangent estimators, are widely used in several different practical application. The second part consist of a proposition and theory of a new methods for solving particular problems. We introduced two new medial axis filtering method. The hierarchical scale medial axis which is based on previously proposed scale axis transform, however, is free of drawbacks introduced in the previously proposed method and the discrete adaptive medial axis where the filtering parameter is dynamically adapted to the local size of the object. In this part we also introduced an efficient and parameter less new tangent estimators along three-dimensional discrete curves, called 3D maximal segment tangent direction. Finally, we showed that discrete geometry and topology algorithms can be useful in the problem of quantitative analysis of the human airway trees based on computed tomography images. According to proposed in the literature design of such system we applied discrete topology and geometry algorithms to solve particular problems at each step of the quantitative analysis process. First, we propose a robust method for segmenting airway tree from CT datasets. The method is based on the tunnel closing algorithm and is used as a tool to repair, damaged by acquisition errors, CT images. We also proposed an algorithm for creation of an artificial model of the bronchial tree and we used such model to validate algorithms presented in this work. Then, we compare the quality of different algorithms using set of experiments conducted on computer phantoms and real CT dataset. We show that recently proposed methods which works in cubical complex framework, together with methods introduced in this work can overcome problems reported in the literature and can be a good basis for the further implementation of the system for automatic quantification of bronchial tree properties

Representações computacionais de formas podem ser criadas em ferramentas CAD ou geradas a partir de um objeto físico já existente. Esta última abordagem oferece como vantagens rapidez e fidelidade ao objeto original, que são os aspectos fundamentais em muitas aplicações, como Simulações Numéricas de Equações Diferenciais Parciais e Imagens Médicas. A reconstrução (ou geração de malhas superficiais) a partir de pontos amostrados de uma superfície de um objeto é um problema clássico de representação de formas. Nesta dissertação apresentamos um vasto levantamento bibliográfico deste tipo de reconstrução, classificando e descrevendo os principais trabalhos presentes na literatura. A partir do levantamento bibliográfico, selecionamos um conjunto de algoritmos sobre os quais foram realizadas comparações teóricas e empíricas cujos resultados são apresentados. Para finalizar, apresentamos aplicações de nossas implementações em Simulação Numérica de Equações Diferenciais Parciais e processamento de Imagens / Computational representations of shapes can be developed using CAD applications or created from data acquired from a real physical object. This latter is advantageous with respect to time and fidelity to the original object which are essential to several applications, such as Numerical Simulation of Partial Differential Equations and Medical Imaging. A classical shape representation problem is that of reconstruction (or superficial mesh generation) from points sampled over the surface of an object. In this Master\'s thesis we describe a broad survey of these reconstruction methods. We focus in the classification and characterization of the main algorithms proposed in the literature. From this survey, we selected some algorithms and conducted some theoretical and practical comparisons. We conclude this work describing applications of the algorithms implemented in Numerical Simulations of Differential Partial Equations and Image Processing

The need for increased product variety and improved aesthetics require the manufacturing enterprise to reduce time to market and to increase use of free-form surfaces in the form of the product. These changes lead to problems in the traditional approach for specification and verification of tolerances especially for a free form surfaces. In the case of freeform surfaces, the desired performance of a product depends on its geometry and is often controlled by intrinsic parameters such as curvature. Design intent therefore requires control on variations in these parameters. Ideally therefore, tolerances have to be applied on these parameters to prescribe allowable variations in the geometry of free-form surfaces. Since only the geometry of the product is controlled in manufacturing, tolerance specification has to ensure that the tolerances specified on the part geometry will ensure that the resulting value of the parameter of interest is within the limits prescribed by the designer. Relationship between allowable range in design parameters and that in geometry is not linear. Tolerance specification therefore becomes a trial and error process requiring considerable expertise and time. This thesis provides designers with a tool to automatically derive the corresponding tolerances to be specified to the manufacturing process to realize the final shape, such that the parameters that are used to control shape of the surface are within the prescribed variations. Automation in acquiring inspection data has brought dramatic changes in procedure for tolerance verification too. Optical scanners and similar non-contact devices provide large amount of points on the surface of the part quite rapidly. The unstructured point data are then processed to determine if the part complies with the given tolerance specifications. For freeform surfaces, current methods of verification uses minimum distance criterion between the nominal surface and unstructured point data. This ignores the correspondence between the points in the two data sets and may result in the rejection of good parts and acceptance of bad parts. There are other unresolved such as the singularity at corners of polyhedral shapes and handling datum. A new approach based on the Medial Axis Transform (MAT) has been proposed. It has been shown that reasoning on the MAT of the nominal model and the measured point set respectively enables the identification of corresponding points in the two sets. Verification of the tolerance allocated is therefore free from the problem mentioned above. MAT exhibits dimensional reduction and hence reduces verification time. It also eliminates surface fitting for detected feature. Results of implementation are provided for tolerance specification and verification using MAT.

Representações computacionais de formas podem ser criadas em ferramentas CAD ou geradas a partir de um objeto físico já existente. Esta última abordagem oferece como vantagens rapidez e fidelidade ao objeto original, que são os aspectos fundamentais em muitas aplicações, como Simulações Numéricas de Equações Diferenciais Parciais e Imagens Médicas. A reconstrução (ou geração de malhas superficiais) a partir de pontos amostrados de uma superfície de um objeto é um problema clássico de representação de formas. Nesta dissertação apresentamos um vasto levantamento bibliográfico deste tipo de reconstrução, classificando e descrevendo os principais trabalhos presentes na literatura. A partir do levantamento bibliográfico, selecionamos um conjunto de algoritmos sobre os quais foram realizadas comparações teóricas e empíricas cujos resultados são apresentados. Para finalizar, apresentamos aplicações de nossas implementações em Simulação Numérica de Equações Diferenciais Parciais e processamento de Imagens / Computational representations of shapes can be developed using CAD applications or created from data acquired from a real physical object. This latter is advantageous with respect to time and fidelity to the original object which are essential to several applications, such as Numerical Simulation of Partial Differential Equations and Medical Imaging. A classical shape representation problem is that of reconstruction (or superficial mesh generation) from points sampled over the surface of an object. In this Master\'s thesis we describe a broad survey of these reconstruction methods. We focus in the classification and characterization of the main algorithms proposed in the literature. From this survey, we selected some algorithms and conducted some theoretical and practical comparisons. We conclude this work describing applications of the algorithms implemented in Numerical Simulations of Differential Partial Equations and Image Processing

Cette thèse s'inscrit dans la problématique de la reconstruction de surfaces à partir de nuages de points. Les récentes avancées faites dans le domaine de l'acquisition de formes 3D à l'aide de scanners donnent lieu à de nouveaux besoins en termes d'algorithmes de reconstruction. Il faut être capable de traiter de grands nuages de points bruités tout en donnant une représentation compacte de la surface reconstruite.<br>La surface est reconstruite comme le niveau zéro d'une fonction. Représenter une surface implicitement en utilisant des fonctions de base radiales (Radial Basis Functions) est devenu une approche standard ces dix dernières années. Une problématique intéressante est la réduction du nombre de fonctions de base pour obtenir une représentation la plus compacte possible et réduire les temps d'évaluation.<br>Réduire le nombre de fonctions de base revient à réduire le nombre de points (centres) sur lesquels elles sont centrées. L'objectif que l'on s'est fixé consiste à sélectionner un "petit" ensemble de centres, les plus pertinents possible. Pour réduire le nombre de centres tout en gardant un maximum d'information, nous nous sommes affranchis de la correspondance entre centres des fonctions et points de donnée, qui est imposée dans la quasi-totalité des approches RBF. Au contraire, nous avons décidé de placer les centres sur l'axe médian de l'ensemble des points de donnée et de montrer que ce choix était approprié.<br>Pour cela, nous avons utilisé les outils donnés par la géométrie algorithmique et approximé l'axe médian par un sous-ensemble des sommets du diagramme de Voronoi des points de donnée. Nous avons aussi proposé deux approches différentes qui échantillonnent de manière appropriée l'axe médian pour adapter le niveau de détail de la surface reconstruite au budget de centres alloué par l'utilisateur.

Cette thèse s´inscrit dans la problématique de la reconstruction de surfaces à partir de nuages de points. Les récentes avancées faites dans le domaine de l´acquisition de formes 3D à l´aide de scanners donnent lieu à de nouveaux besoins en termes d´algorithmes de reconstruction. Il faut être capable de traiter de grands nuages de points bruités tout en donnant une représentation compacte de la surface reconstruite. La surface est reconstruite comme le niveau zéro d´une fonction. Représenter une surface implicitement en utilisant des fonctions de base radiales (Radial Basis Functions) est devenu une approche standard ces dix dernières années. Une problématique intéressante est la réduction du nombre de fonctions de base pour obtenir une représentation la plus compacte possible et réduire les temps d´évaluation. Réduire le nombre de fonctions de base revient à réduire le nombre de points (centres) sur lesquels elles sont centrées. L´objectif que l´on s´est fixé consiste à sélectionner un "petit" ensemble de centres, les plus pertinents possible. Pour réduire le nombre de centres tout en gardant un maximum d´information, nous nous sommes affranchis de la correspondance entre centres des fonctions et points de donnée, qui est imposée dans la quasi-totalité des approches RBF. Au contraire, nous avons décidé de placer les centres sur l´axe médian de l´ensemble des points de donnée et de montrer que ce choix était approprié. Pour cela, nous avons utilisé les outils donnés par la géométrie algorithmique et approximé l´axe médian par un sous-ensemble des sommets du diagramme de Voronoi des points de donnée. Nous avons aussi proposé deux approches diférentes qui échantillonnent de manière appropriée l´axe médian pour adapter le niveau de détail de la surface reconstruite au budget de centres alloué par l´utilisateur.

Heterogeneous Objects are engineered with multiple materials to achieve multiple functionalities like high hardness, high toughness and low structural weight. Heterogeneous objects are increasingly used to achieve multiple and often conflicting behaviour within a single object. Developing heterogeneous objects needs computational model for design, analysis and manufacturing. The computational model should map the geometry of the object with the material composition. The most general model is the volume based model that decomposes the geometry exhaustively into simple elements and defines the material distribution over these elements. This approach can model a wide range of objects. However, defining material distribution needs manual intervention to select these elements for material continuity, and to segment or subdivide them for better material approximation. Volume based representation is quite large in size and is cumbersome to edit, query or reuse. Feature based approaches have been proposed to address some of these issues. However, current art can model only limited class of Heterogeneous Objects that includes simple material distribution over complex geometry or complex material distribution over simple geometry. The thesis presents a new method to overcome these limitations. The method, a hybrid of volume based and feature based approaches, allows the user to define the complex material distribution over complex geometries intuitively and represent the same. The complex material distribution is modelled using material reference entities that may be mixed-dimensional, inclusive of non-manifold entities. It uses Medial Axis Transform for automated segmentation of these entities into independent regions, where the material distribution can be intuitively prescribed starting from the entity and terminating at the medial axis. The spatial variation of the material is captured by a parameterized distance field from the material reference entities. It develops new constructive operators to build a complex heterogeneous object model that allows the reuse of the existing heterogeneous object models, automates handling of material continuity, and controls the gradation of the material in the interface of the constituent heterogeneous objects. Constructions using these operators can be geometry driven or material driven i.e. the geometric form controls the material distribution or the material distribution is independent of the geometric form. The proposed representation can be adaptively meshed for generation of mesh in the direction of gradation of the material for finite element analysis and process planning for additive manufacturing. An iso-material contour representation has been proposed for process planning of Heterogeneous Object Models. This avoids the stair case effect by depositing material in the direction of material gradation, and avoids over-deposition or under-deposition due to frequent start and stop of the nozzles. The proposed method has been implemented to show that it can model wide range of heterogeneous objects and can be integrated with additive manufacturing.

La tomodensitométrie est une technique très utile qui permet de mener avec succès des analyses non-invasives dans plusieurs types d'applications, par exemple médicales ou industrielles. L'analyse manuelle des structures d'intérêt présentes dans une image peut prendre beaucoup de temps, être laborieuse et parfois même impossible à faire en raison de sa complexité. C'est pour cela que dans cette thèse, nous proposons et développons des algorithmes nécessaires à cette analyse, basés sur la géométrie discrète et la topologie. Ces algorithmes peuvent servir dans de nombreuses applications, et en particulier au niveau de l'analyse quantitative automatique de l'arbre bronchique humain, sur la base d'images de tomodensitométrie. La première partie introduit les notions fondamentales de la topologie et de la géométrie discrètes utiles dans cette thèse. Ensuite, nous présentons le principe de méthodes utilisées dans de nombreuses applications : les algorithmes de squelettisation, de calcul de l'axe médian, les algorithmes de fermeture de tunnels et les estimateurs de tangentes. La deuxième partie présente les nouvelles méthodes que nous proposons et qui permettent de résoudre des problèmes particuliers. Nous avons introduit deux méthodes nouvelles de filtrage d'axe médian. La première, que nous appelons "hierarchical scale medial axis", est inspirée du "scale axis transform", sans les inconvénients qui sont propres à la méthode originale. La deuxième est une méthode nommée "discrete adaptive medial axis", où le paramètre de filtrage est adapté dynamiquement aux dimensions locales de l'objet. Dans cette partie, nous introduisons également des estimateurs de tangente nouveaux et efficaces, agissant sur des courbes discrètes tridimensionnelles, et que nous appelons "3Dlambda maximal segment tangent direction". Enfin, nous avons montré que la géométrie discrète et les algorithmes topologiques pouvaient être utiles dans le problème de l'analyse quantitative de l'arbre bronchique humain à partir d'images tomodensitométriques. Dans une chaîne de traitements de structure classique par rapport à l'état de l'art, nous avons appliqué des méthodes de topologie et de géométrie discrète afin de résoudre des problèmes particuliers dans chaque étape du processus de l'analyse quantitative. Nous proposons une méthode robuste pour segmenter l'arbre bronchique à partir d'un ensemble de données tomographiques (CT). La méthode est basée sur un algorithme de fermeture de tunnels qui est utilisé comme outil pour réparer des images CT abîmées par les erreurs d'acquisition. Nous avons aussi proposé un algorithme qui sert à créer un modèle artificiel d'arbre bronchique. Ce modèle est utilisé pour la validation des algorithmes présentés dans cette thèse. Ensuite nous comparons la qualité des différents algorithmes en utilisant un ensemble de test constitué de fantômes (informatiques) et d'un ensemble de données CT réelles. Nous montrons que les méthodes récemment présentées dans le cadre des complexes cubiques, combinées avec les méthodes présentées dans cette thèse, permettent de surmonter des problèmes indiqués par la littérature et peuvent être un bon fondement pour l'implémentation future des systèmes de quantification automatique des particularités de l'arbre bronchique / Computed tomography is a very useful technic which allow non-invasive diagnosis in many applications for example is used with success in industry and medicine. However, manual analysis of the interesting structures can be tedious and extremely time consuming, or even impossible due its complexity. Therefore in this thesis we study and develop discrete geometry and topology algorithms suitable for use in many practical applications, especially, in the problem of automatic quantitative analysis of the human airway trees based on computed tomography images. In the first part, we define basic notions used in discrete topology and geometry then we showed that several class of discrete methods like skeletonisation algorithms, medial axes, tunnels closing algorithms and tangent estimators, are widely used in several different practical application. The second part consist of a proposition and theory of a new methods for solving particular problems. We introduced two new medial axis filtering method. The hierarchical scale medial axis which is based on previously proposed scale axis transform, however, is free of drawbacks introduced in the previously proposed method and the discrete adaptive medial axis where the filtering parameter is dynamically adapted to the local size of the object. In this part we also introduced an efficient and parameter less new tangent estimators along three-dimensional discrete curves, called 3D maximal segment tangent direction. Finally, we showed that discrete geometry and topology algorithms can be useful in the problem of quantitative analysis of the human airway trees based on computed tomography images. According to proposed in the literature design of such system we applied discrete topology and geometry algorithms to solve particular problems at each step of the quantitative analysis process. First, we propose a robust method for segmenting airway tree from CT datasets. The method is based on the tunnel closing algorithm and is used as a tool to repair, damaged by acquisition errors, CT images. We also proposed an algorithm for creation of an artificial model of the bronchial tree and we used such model to validate algorithms presented in this work. Then, we compare the quality of different algorithms using set of experiments conducted on computer phantoms and real CT dataset. We show that recently proposed methods which works in cubical complex framework, together with methods introduced in this work can overcome problems reported in the literature and can be a good basis for the further implementation of the system for automatic quantification of bronchial tree properties