La modification de la structure des matériaux par Détente Instantanée Contrôlée (DIC), implique nécessairement un processus d’autovaporisation instantanée en conditions thermodynamiques extrêmes de surchauffe du liquide. Les divers processus DIC de modification de la structure par expansion contrôlée, d’extraction et de refroidissement instantané sont d’un intérêt particulier. Les conditions opératoires et les caractéristiques spécifiques du produit interagissent mutuellement pour aboutir au meilleur résultat, principalement en termes de texture. Les modifications des caractéristiques structurelles généralement traduites par des taux d’expansion du produit, dépendent donc des conditions opératoires et des propriétés thermiques et rhéologiques de la matière. De nombreuses études initiales ont montré l’intérêt de déterminer l’évolution des divers processus à travers un suivi et un enregistrement instantané des images, des températures et de la pression à l’échelle de 1000 unités par seconde ; il a ainsi été indispensable de mettre en opération une caméra ultra rapide à 1000 images / s, des capteurs de température et de pression à temps de réponse de l’ordre du ms, placés dans le réacteur et au sein du produit. Une analyse fondamentale a prouvé l’importance de la thermodynamique, du transfert et de la problématique d’expansion pendant le traitement. L’analyse des expériences est réalisée par la détermination des taux d’expansion, surfacique et volumique, de la durée du processus d’expansion proprement dite, de l’analyse des caractéristiques micro-structurelles par MEB, mais principalement par la détermination de la température de transition vitreuse, de la différence de température minimale et d’ébullition, et du taux d’échange de chaleur. Plusieurs produits ont été étudiés (fromage, tofu, pomme, pomme de terre, carotte et banane). Des essais préliminaires adéquats ont permis d’identifier les domaines de variation des paramètres opératoires et d’adopter la méthode des plans d’expériences rota tables à cinq niveaux pour quantifier les diverses réponses nécessaires. / The structural modification of materials by the process of instant controlled pressure drop (DIC), is mainly based on the instant autovaporization process in very far from thermodynamic equilibrium conditions. The structure modification process and the volume evolution strictly depend on DIC operational parameters and the product characteristics mutually interacting to achieve the objective in terms of texture.The change in the structural characteristics of the product is generally revealed through the expansion rates of the product ; it depends on the operating conditions. This study will use a snapshot taken by a high speed video camera 1000 fps, coupled with 1 ms response temperature and pressure sensors, placed in the treatment vessel and inside the product. A fundamental analysis has proved the importance of thermodynamics, the transfer and the specific problematic of expansion during treatment. Study was carried out by determining the3D expansion ratio, the 2D surface expansion ratio, and the volumetric expansion ratio, as well as the durations of expansion just after pressure drops, the analysis of SEM micro-structural characteristics, the different glass transition temperatures Tg, the differences between lowest product and reactor temperatures and boiling temperature, and the heat exchange rate. Various products were considered (cheese, tofu, apple, potato, carrot and banana). The preliminary tests with each have led us to identify the relevant operating parameter ranges. Different fundamental conclusions and industrial application could be thus defined.

Three dimensional mapping is becoming an increasingly attractive product nowadays. Many devices like laser scanner or stereo systems provide 3D scene reconstruction. A new type of active sensor, the Time of Flight (ToF) camera obtains direct depth observations (3rd dimensional coordinate) in a high video rate, useful for interactive robotic and navigation applications. The high frame rate combined with the low weight and the compact design of the ToF cameras constitute an alternative solution of the 3D measuring technology. However a deep understanding of the error involved in the ToF camera observations is essential in order to upgrade their accuracy and enhance the ToF camera performance. This thesis work addresses the depth error characteristics of the SR4000 ToF camera and indicates potential error models for compensating the impact. In the beginning of the work the thesis investigates the error sources, their characteristics and how they influence the depth measurements. In the practical part, the work covers the above analysis via experiments. Last, the work proposes simple methods in order to reduce the depth error so that the ToF camera can be used for high accuracy applications.   An overall result of the work indicates that the depth acquired by the Time of Flight (ToF) camera deviates several centimeters, specifically the SR4000 camera provides 35 cm error size for the working range of 1-8 m. After the error compensation the depth offset fluctuates 15cm within the same working range. The error is smaller when the camera is set up close to the test field than when it is further away.

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This thesis presents a method of tracking and correcting for the swaying of a central receiver tower in concentrated solar production plants. The method uses a camera with image processing algorithms to detect movement of the center of the tower. A prototype was constructed utilizing a CMOS camera connected to a microcontroller to control the movements of three surrounding heliostats. The prototype uses blob-tracking algorithms to detect and correct for movements of a colored model target. The model was able to detect movements in the tower with average error of 0.32 degrees, and was able to correctly orient the surrounding heliostats to within 1.2 and 2.6 degrees of accuracy while testing indoors and outdoors, respectively.

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Assessment of finger range of motion (ROM) is often required for monitoring the effectiveness of rehabilitative treatments and for evaluating patients' functional impairment. There are several devices which are used to measure this motion, such as wire tracing, tracing onto paper and mechanical and electronic goniometry. These devices are quite cheap, excluding electronic goniometry; however the drawbacks of these devices are their lack of accuracy and the time- consuming nature of the measurement process. The work described in this thesis considers the design, implementation and validation of a new medical measurement system utilized in the evaluation of the range of motion of the human finger joints instead of the current measurement tools. The proposed system is a non-contact measurement device based on computer vision technology and has many advantages over the existing measurement devices. In terms of accuracy, better results are achieved by this system, it can be operated by semi-skilled person, and is time saving for the evaluator. The computer vision system in this study consists of CCD cameras to capture the images, a frame-grabber to change the analogue signal from the cameras to digital signals which can be manipulated by a computer, Ultra Violet light (UV) to illuminate the measurement space, software to process the images and perform the required computation, a darkened enclosure to accommodate the cameras and UV light and to shield the working area from any undesirable ambient light. Two calibration techniques were used to calibrate the cameras, Direct Linear Transformation and Tsai. A calibration piece that suits this application was designed and manufactured. A steel hand model was used to measure the fingers joint angles. The average error from measuring the finger angles using this system was around 1 degree compared with 5 degrees for the existing used techniques.

This thesis considers the problem of tracking an object in world coordinates using measurements obtained from multiple uncalibrated cameras. A general approach to track the location of a target involves different phases including calibrating the camera, detecting the object's feature points over frames, tracking the object over frames and analyzing object's motion and behavior. The approach contains two stages. First, the problem of camera calibration using a calibration object is studied. This approach retrieves the camera parameters from the known locations of ground data in 3D and their corresponding image coordinates. The next important part of this work is to develop an automated system to estimate the trajectory of the object in 3D from image sequences. This is achieved by combining, adapting and integrating several state-of-the-art algorithms. Synthetic data based on a nearly constant velocity object motion model is used to evaluate the performance of camera calibration and state estimation algorithms.

<div>Numerous organizations around the world deploy sensor networks, especially visual sensor networks for various applications like monitoring traffic, security, and emergencies. With advances in computer vision technology, the potential application of these sensor networks has expanded. This has led to an increase in demand for deployment of large scale sensor networks.</div><div>Sensors in a large network have differences in location, position, hardware, etc. These differences lead to varying usefulness as they provide different quality of information. As an example, consider the cameras deployed by the Department of Transportation (DOT). We want to know whether the same traffic cameras could be used for monitoring the damage by a hurricane.</div><div>Presently, significant manual effort is required to identify useful sensors for different applications. There does not exist an automated system which determines the usefulness of the sensors based on the application. Previous methods on visual sensor networks focus on finding the dependability of sensors based on only the infrastructural and system issues like network congestion, battery failures, hardware failures, etc. These methods do not consider the quality of information from the sensor network. In this paper, we present an automated system which identifies the most useful sensors in a network for a given application. We evaluate our system on 2,500 real-time live sensors from four cities for traffic monitoring and people counting applications. We compare the result of our automated system with the manual score for each camera.</div><div>The results suggest that the proposed system reliably finds useful sensors and it output matches the manual scoring system. It also shows that a camera network deployed for a certain application can also be useful for another application.</div>