945 resultados para three-dimensional continuun-mechanical image-warping


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Problématique. L'utilisation d'un chien d'assistance à la mobilité (CAM) représente une option novatrice pour préserver l’intégrité des membres supérieurs (MSs) chez les utilisateurs de fauteuil roulant manuel (FRM). Aucune étude biomécanique n’a quantifié les effets du CAM sur les efforts aux MSs lors de la montée d’un plan incliné. Objectif. Cette étude quasi-expérimentale vise à comparer les efforts aux MSs lors de la montée d’un plan incliné avec et sans l’assistance d’un CAM. Méthodologie. Dix participants avec une lésion de la moelle épinière (LME) qui utilisent un FRM et possèdent un CAM ont monté un plan incliné à trois reprises avec et sans l’assistance du CAM. Les forces appliquées sur les cerceaux, mesurées avec des roues instrumentées, et les mouvements du FRM et des MSs, enregistrés avec un système d'analyse du mouvement, ont permis de mesurer les efforts mécaniques aux MSs. Simultanément, l'activité électromyographique (EMG) des muscles grand pectoral, deltoïde antérieur, biceps et triceps a été enregistrée et normalisée avec sa valeur maximale pour mesurer les efforts musculaires aux MSs. Résultats. En général, le CAM réduit significativement les valeurs moyennes et maximales de la force totale appliquée aux cerceaux et de sa composante tangentielle, des moments nets de flexion, de rotation interne et d’adduction aux épaules et des taux d’utilisation musculaire du deltoïde antérieur, du biceps et du triceps. Conclusion. L’assistance d’un CAM réduit les efforts aux MSs lors de la montée d’un plan incliné chez les utilisateurs d’un FRM ayant une LME.

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There are many ways to generate geometrical models for numerical simulation, and most of them start with a segmentation step to extract the boundaries of the regions of interest. This paper presents an algorithm to generate a patient-specific three-dimensional geometric model, based on a tetrahedral mesh, without an initial extraction of contours from the volumetric data. Using the information directly available in the data, such as gray levels, we built a metric to drive a mesh adaptation process. The metric is used to specify the size and orientation of the tetrahedral elements everywhere in the mesh. Our method, which produces anisotropic meshes, gives good results with synthetic and real MRI data. The resulting model quality has been evaluated qualitatively and quantitatively by comparing it with an analytical solution and with a segmentation made by an expert. Results show that our method gives, in 90% of the cases, as good or better meshes as a similar isotropic method, based on the accuracy of the volume reconstruction for a given mesh size. Moreover, a comparison of the Hausdorff distances between adapted meshes of both methods and ground-truth volumes shows that our method decreases reconstruction errors faster. Copyright © 2015 John Wiley & Sons, Ltd.

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Three dimensional (3D) composites are strong contenders for the structural applications in situations like aerospace,aircraft and automotive industries where multidirectional thermal and mechanical stresses exist. The presence of reinforcement along the thickness direction in 3D composites,increases the through the thickness stiffness and strength properties.The 3D preforms can be manufactured with numerous complex architecture variations to meet the needs of specific applications.For hot structure applications Carbon-Carbon(C-C) composites are generally used,whose property variation with respect to temperature is essential for carrying out the design of hot structures.The thermomechanical behavior of 3D composites is not fully understood and reported.The methodology to find the thermomechanical properties using analytical modelling of 3D woven,3D 4-axes braided and 3D 5-axes braided composites from Representative Unit Cells(RUC's) based on constitutive equations for 3D composites has been dealt in the present study.High Temperature Unidirectional (UD) Carbon-Carbon material properties have been evaluated using analytical methods,viz.,Composite cylinder assemblage Model and Method of Cells based on experiments carried out on Carbon-Carbon fabric composite for a temparature range of 300 degreeK to 2800degreeK.These properties have been used for evaluating the 3D composite properties.From among the existing methods of solution sequences for 3D composites,"3D composite Strength Model" has been identified as the most suitable method.For thegeneration of material properies of RUC's od 3D composites,software has been developed using MATLAB.Correlaton of the analytically determined properties with test results available in literature has been established.Parametric studies on the variation of all the thermomechanical constants for different 3D performs of Carbon-Carbon material have been studied and selection criteria have been formulated for their applications for the hot structures.Procedure for the structural design of hot structures made of 3D Carbon-Carbon composites has been established through the numerical investigations on a Nosecap.Nonlinear transient thermal and nonlinear transient thermo-structural analysis on the Nosecap have been carried out using finite element software NASTRAN.Failure indices have been established for the identified performs,identification of suitable 3D composite based on parametric studies on strength properties and recommendation of this material for Nosecap of RLV based on structural performance have been carried out in this Study.Based on the 3D failure theory the best perform for the Nosecap has been identified as 4-axis 15degree braided composite.

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One of the interesting consequences of Einstein's General Theory of Relativity is the black hole solutions. Until the observation made by Hawking in 1970s, it was believed that black holes are perfectly black. The General Theory of Relativity says that black holes are objects which absorb both matter and radiation crossing the event horizon. The event horizon is a surface through which even light is not able to escape. It acts as a one sided membrane that allows the passage of particles only in one direction i.e. towards the center of black holes. All the particles that are absorbed by black hole increases the mass of the black hole and thus the size of event horizon also increases. Hawking showed in 1970s that when applying quantum mechanical laws to black holes they are not perfectly black but they can emit radiation. Thus the black hole can have temperature known as Hawking temperature. In the thesis we have studied some aspects of black holes in f(R) theory of gravity and Einstein's General Theory of Relativity. The scattering of scalar field in this background space time studied in the first chapter shows that the extended black hole will scatter scalar waves and have a scattering cross section and applying tunneling mechanism we have obtained the Hawking temperature of this black hole. In the following chapter we have investigated the quasinormal properties of the extended black hole. We have studied the electromagnetic and scalar perturbations in this space-time and find that the black hole frequencies are complex and show exponential damping indicating the black hole is stable against the perturbations. In the present study we show that not only the black holes exist in modified gravities but also they have similar properties of black hole space times in General Theory of Relativity. 2 + 1 black holes or three dimensional black holes are simplified examples of more complicated four dimensional black holes. Thus these models of black holes are known as toy models of black holes in four dimensional black holes in General theory of Relativity. We have studied some properties of these types of black holes in Einstein model (General Theory of Relativity). A three dimensional black hole known as MSW is taken for our study. The thermodynamics and spectroscopy of MSW black hole are studied and obtained the area spectrum which is equispaced and different thermo dynamical properties are studied. The Dirac perturbation of this three dimensional black hole is studied and the resulting quasinormal spectrum of this three dimensional black hole is obtained. The different quasinormal frequencies are tabulated in tables and these values show an exponential damping of oscillations indicating the black hole is stable against the mass less Dirac perturbation. In General Theory of Relativity almost all solutions contain singularities. The cosmological solution and different black hole solutions of Einstein's field equation contain singularities. The regular black hole solutions are those which are solutions of Einstein's equation and have no singularity at the origin. These solutions possess event horizon but have no central singularity. Such a solution was first put forward by Bardeen. Hayward proposed a similar regular black hole solution. We have studied the thermodynamics and spectroscopy of Hay-ward regular black holes. We have also obtained the different thermodynamic properties and the area spectrum. The area spectrum is a function of the horizon radius. The entropy-heat capacity curve has a discontinuity at some value of entropy showing a phase transition.

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The consumers are becoming more concerned about food quality, especially regarding how, when and where the foods are produced (Haglund et al., 1999; Kahl et al., 2004; Alföldi, et al., 2006). Therefore, during recent years there has been a growing interest in the methods for food quality assessment, especially in the picture-development methods as a complement to traditional chemical analysis of single compounds (Kahl et al., 2006). The biocrystallization as one of the picture-developing method is based on the crystallographic phenomenon that when crystallizing aqueous solutions of dihydrate CuCl2 with adding of organic solutions, originating, e.g., from crop samples, biocrystallograms are generated with reproducible crystal patterns (Kleber & Steinike-Hartung, 1959). Its output is a crystal pattern on glass plates from which different variables (numbers) can be calculated by using image analysis. However, there is a lack of a standardized evaluation method to quantify the morphological features of the biocrystallogram image. Therefore, the main sakes of this research are (1) to optimize an existing statistical model in order to describe all the effects that contribute to the experiment, (2) to investigate the effect of image parameters on the texture analysis of the biocrystallogram images, i.e., region of interest (ROI), color transformation and histogram matching on samples from the project 020E170/F financed by the Federal Ministry of Food, Agriculture and Consumer Protection(BMELV).The samples are wheat and carrots from controlled field and farm trials, (3) to consider the strongest effect of texture parameter with the visual evaluation criteria that have been developed by a group of researcher (University of Kassel, Germany; Louis Bolk Institute (LBI), Netherlands and Biodynamic Research Association Denmark (BRAD), Denmark) in order to clarify how the relation of the texture parameter and visual characteristics on an image is. The refined statistical model was accomplished by using a lme model with repeated measurements via crossed effects, programmed in R (version 2.1.0). The validity of the F and P values is checked against the SAS program. While getting from the ANOVA the same F values, the P values are bigger in R because of the more conservative approach. The refined model is calculating more significant P values. The optimization of the image analysis is dealing with the following parameters: ROI(Region of Interest which is the area around the geometrical center), color transformation (calculation of the 1 dimensional gray level value out of the three dimensional color information of the scanned picture, which is necessary for the texture analysis), histogram matching (normalization of the histogram of the picture to enhance the contrast and to minimize the errors from lighting conditions). The samples were wheat from DOC trial with 4 field replicates for the years 2003 and 2005, “market samples”(organic and conventional neighbors with the same variety) for 2004 and 2005, carrot where the samples were obtained from the University of Kassel (2 varieties, 2 nitrogen treatments) for the years 2004, 2005, 2006 and “market samples” of carrot for the years 2004 and 2005. The criterion for the optimization was repeatability of the differentiation of the samples over the different harvest(years). For different samples different ROIs were found, which reflect the different pictures. The best color transformation that shows efficiently differentiation is relied on gray scale, i.e., equal color transformation. The second dimension of the color transformation only appeared in some years for the effect of color wavelength(hue) for carrot treated with different nitrate fertilizer levels. The best histogram matching is the Gaussian distribution. The approach was to find a connection between the variables from textural image analysis with the different visual criteria. The relation between the texture parameters and visual evaluation criteria was limited to the carrot samples, especially, as it could be well differentiated by the texture analysis. It was possible to connect groups of variables of the texture analysis with groups of criteria from the visual evaluation. These selected variables were able to differentiate the samples but not able to classify the samples according to the treatment. Contrarily, in case of visual criteria which describe the picture as a whole there is a classification in 80% of the sample cases possible. Herewith, it clearly can find the limits of the single variable approach of the image analysis (texture analysis).

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Enhanced reality visualization is the process of enhancing an image by adding to it information which is not present in the original image. A wide variety of information can be added to an image ranging from hidden lines or surfaces to textual or iconic data about a particular part of the image. Enhanced reality visualization is particularly well suited to neurosurgery. By rendering brain structures which are not visible, at the correct location in an image of a patient's head, the surgeon is essentially provided with X-ray vision. He can visualize the spatial relationship between brain structures before he performs a craniotomy and during the surgery he can see what's under the next layer before he cuts through. Given a video image of the patient and a three dimensional model of the patient's brain the problem enhanced reality visualization faces is to render the model from the correct viewpoint and overlay it on the original image. The relationship between the coordinate frames of the patient, the patient's internal anatomy scans and the image plane of the camera observing the patient must be established. This problem is closely related to the camera calibration problem. This report presents a new approach to finding this relationship and develops a system for performing enhanced reality visualization in a surgical environment. Immediately prior to surgery a few circular fiducials are placed near the surgical site. An initial registration of video and internal data is performed using a laser scanner. Following this, our method is fully automatic, runs in nearly real-time, is accurate to within a pixel, allows both patient and camera motion, automatically corrects for changes to the internal camera parameters (focal length, focus, aperture, etc.) and requires only a single image.

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Building robust recognition systems requires a careful understanding of the effects of error in sensed features. Error in these image features results in a region of uncertainty in the possible image location of each additional model feature. We present an accurate, analytic approximation for this uncertainty region when model poses are based on matching three image and model points, for both Gaussian and bounded error in the detection of image points, and for both scaled-orthographic and perspective projection models. This result applies to objects that are fully three- dimensional, where past results considered only two-dimensional objects. Further, we introduce a linear programming algorithm to compute the uncertainty region when poses are based on any number of initial matches. Finally, we use these results to extend, from two-dimensional to three- dimensional objects, robust implementations of alignmentt interpretation- tree search, and ransformation clustering.

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Creació d'un entorn de treball per tal de visualitzar models tridimensionals en temps real amb dos objectius: proporcionar una interfície gràfica per poder visualitzar interactivament una escena, modificant-ne els seus elements i aconseguir un disseny que faci el projecte altament revisable i reutilitzable en el futur, i serveixi per tant de plataforma per provar altres projectes

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L’objectiu d’aquest PFC és el desenvolupament d’una eina pel modelatge procedural d’edificis i altres estructures arquitectòniques. El modelatge d’edificis és, per si sol, un bon tema on aplicar‐hi la programació procedural. Un edifici normal compte sempre amb elements que es repeteixen en altura i amplada. El fet de “repetir” una tasca suggereix sempre l’aplicació d’algun tipus de procediment per tal de simplificar i reduir la feina de l’usuari a l’hora de desenvolupar aquesta feina

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Aquest projecte es basarà en reconstruir una imatge 3D gran a partir d’una seqüència d’imatges 2D capturades per una càmera. Ens centrem en l’estudi de les bases matemàtiques de la visió per computador així com en diferents mètodes emprats en la reconstrucció 3D d’imatges. Per portar a terme aquest estudi s’utilitza la plataforma de desenvolupament MatLab ja que permet tractar operacions matemàtiques, imatges i matrius de gran tamany amb molta senzillesa, rapidesa i eficiència, per aquesta raó s’usa en moltes recerques sobre aquest tema. El projecte aprofundeix en el tema descrit anteriorment estudiant i implementant un mètode que consisteix en aplicar Structure From Motion (SFM) a pocs frames seguits obtinguts d’una seqüència d’imatges 2D per crear una reconstrucció 3D. Quan s’han creat dues reconstruccions 3D consecutives i fent servir un frame com a mínim en comú entre elles, s’aplica un mètode de registre d’estructures 3D, l’Iterative Closest Point (ICP), per crear una reconstrucció 3D més gran a través d’unir les diferents reconstruccions obtingudes a partir de SfM. El mètode consisteix en anar repetint aquestes operacions fins al final dels frames per poder aconseguir una reconstrucció 3D més gran que les petites imatges que s’aconsegueixen a través de SfM. A la Figura 1 es pot veure un esquema del procés que es segueix. Per avaluar el comportament del mètode, utilitzem un conjunt de seqüències sintètiques i un conjunt de seqüències reals obtingudes a partir d’una càmera. L’objectiu final d’aquest projecte és construir una nova toolbox de MatLab amb tots els mètodes per crear reconstruccions 3D grans per tal que sigui possible tractar amb facilitat aquest problema i seguir-lo desenvolupant en un futur

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L’objectiu principal d’aquest projecte era implementar la visualització 3D de models fusionats i aplicar totes les tècniques possibles per realitzar aquesta fusió. Aquestes tècniques s’integraran en la plataforma de visualització i processament de dades mèdiques STARVIEWER. Per assolir l’ objectiu principal s’ han definit els següents objectius específics:1- estudiar els algoritmes de visualització de models simples i analitzar els diferents paràmetres a tenir en compte. 2- ampliació de la tècnica de visualització bàsica seleccionada per tal de suportar els models fusionats. 3- avaluar i compar tots els mètodes implementats per poder determinar quin ofereix les millors visualitzacions

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L’estudi consta de dues grans parts que serien la part de dissenyar, desenvolupar i implementar els mètodes de segmentació que ens serviran per separar els punts rígids dels punts no rígids/deformables. I l’altra part seria la d’obtenir reconstruccions 3D a partir d’un sistema estèreo, passant per la calibració de les càmeres del sistema, la realització de captures d’experiments reals, la generació de reconstruccions 3D per finalment posar a prova els mètodes desenvolupats en la part anterior

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El projecte consisteix en analitzar, dissenyar i desenvolupar un sistema estèreo binocular (format per dues càmeres) sobre un suport que ofereixi la mobilitat i portabilitat necessària per utilitzar-lo de forma independent, és a dir, sense necessitat de connexió a un ordinador, ja que normalment, els sistemes de visió per computador solen incorporar un ordinador amb un frame grabber (placa de captura d’imatges). Per a dur a terme el sistema estèreo més adient, s’analitzaran els requeriments necessaris, s’estudiaran diferents alternatives, i finalment, es desenvoluparà i es demostrarà el funcionament del sistema en qüestió

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Seafloor imagery is a rich source of data for the study of biological and geological processes. Among several applications, still images of the ocean floor can be used to build image composites referred to as photo-mosaics. Photo-mosaics provide a wide-area visual representation of the benthos, and enable applications as diverse as geological surveys, mapping and detection of temporal changes in the morphology of biodiversity. We present an approach for creating globally aligned photo-mosaics using 3D position estimates provided by navigation sensors available in deep water surveys. Without image registration, such navigation data does not provide enough accuracy to produce useful composite images. Results from a challenging data set of the Lucky Strike vent field at the Mid Atlantic Ridge are reported

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The accuracy of a 3D reconstruction using laser scanners is significantly determined by the detection of the laser stripe. Since the energy pattern of such a stripe corresponds to a Gaussian profile, it makes sense to detect the point of maximum light intensity (or peak) by computing the zero-crossing point of the first derivative of such Gaussian profile. However, because noise is present in every physical process, such as electronic image formation, it is not sensitive to perform the derivative of the image of the stripe in almost any situation, unless a previous filtering stage is done. Considering that stripe scanning is an inherently row-parallel process, every row of a given image must be processed independently in order to compute its corresponding peak position in the row. This paper reports on the use of digital filtering techniques in order to cope with the scanning of different surfaces with different optical properties and different noise levels, leading to the proposal of a more accurate numerical peak detector, even at very low signal-to-noise ratios