This master's thesis will take us through theoretical procedure that allows us to determine the distance of an object by stereoscopic sensor. Part of this work presents the description of the steps to achieve image of objects, calibraton and rectification. At the next part our study provides an overview of algortihms for creating disparity maps and determining the distance of the object from sensor. In the following part of thesis deals with the implementation of these processes into aplication which aim is to measure the distance.

This master's thesis will take us through theoretical procedure that allows us to determine the distance of an object by stereoscopic sensor. Part of this work presents the description of the steps to achieve image of objects, calibraton and rectification. At the next part our study provides an overview of algortihms for creating disparity maps and determining the distance of the object from sensor. In the following part of thesis deals with the implementation of these processes into aplication which aim is to measure the distance.

This master's thesis deals with determination of properties of the ultrasonic sensor SRF05. It is about finding factors that distort or have other negative effects in any way on the proper functionality of these sensors. First of all, it was necessary to program a chip mounted on signal processing board for correct functionality and operation of sensors. Then a few sets of measurements were done to determine the behaviour of sensors for different distances. In addition, we had to carry out many more measurements to find out the influence of temperature, light conditions, material of the sensed surface or cross-noise caused by the use of multiple sensors. In the next step, the approximate shape of the transmitted ultrasound was investigated to determine the zone of detection. The last task of this thesis was to compare the SRF05 sensors with other ultrasonic sensors from different manufacturers.

Die vorliegende Arbeit hat die Entwicklung und Validierung eines Analysealgorithmus zur objektiven Auswertung der Materialverteilung entlang der Zarge an gezogenen Karton-formziehteilen zum Ziel. Die dafür verwendeten Messdaten werden durch Oberflächenab-tastung mit konfokaler Sensorik erzeugt. Unter Anwendung des Analysealgorithmus wer-den die Einflüsse der Prozessparameter auf die Materialverteilung ermittelt. Abschließend wird aus den gewonnenen Daten ein Ansatz zur Berechnung der Werkzeuggeometrie ent-wickelt. Zur Bestimmung der Materialverteilung wird die Zarge beidseitig abgetastet. Aus der Diffe-renz der Radien von Außen- und Innenkontur wird der Dickenverlauf entlang der Zarge bestimmt, die die Materialverteilung beschreibt. Die Messung mit konfokalen Sensoren wird mit mikroskopischen Aufnahmen von Mikrotomschnitten und röntgentomographi-schen Aufnahmen geprüft. Der Mittelwert und die Standardabweichung des Dickenverlaufs charakterisieren die Mate-rialverteilung. Der Analysealgorithmus ermittelt aus den durch Sensoren aufgenommenen Daten die charakteristischen Werte. In der Auswertung zeigt sich, dass eine Höhere Zieh-stempeltemperatur als Ziehbüchsentemperatur sowie eine hohe Temperatursumme die mittlere Dicke verringern. Eine hohe Faltenhalterkraft und eine hohe Stempeltemperatur bewirken eine gleichmäßigere Materialverteilung. Der ermittelte Zusammenhang von der Beeinflussung des Mittelwertes der Dicke mit den Temperaturunterschieden von Stempel und Büchse wird durch ein Modell der thermischen Ausdehnung von Stempel und Büchse belegt. / The present thesis comprises the development and validation of an algorithm for the objec-tive evaluation of data on material distribution alongside the architrave of drawn cardboard shells. The necessary data are obtained through detection of the surface with confocal sensors. The influences of the process parameters on material distribution are investigated with algorithm. Resulting from this data, the basis for the calculation of the tools geometry is developed. The determination of material distribution is accomplished by double-sided optical scanning of the architraves inner and outer surface. The trend of cardboard thickness alongside the architrave is calculated by the subtracion of the inside radius from the outside radius of the cardboard shell. The cardboard thickness describes material distribution. The measures with confocal sensors are approved of examined microtome cuts under microscope and x-ray analyses. Material distribution is characterised by average of the thickness and standard deviation of thickness. The analysis algorithm calculates with sensor data the characteristic values. A higher temprature of the drawing die as the temprature of the drawing box and the sum of temperatures lead to a decrease of the average thickness. The combination of a high die temperature and a high force applied by the blankholder result in a more even material distribution. The identified correlation of average thickness and temperature gradients between the drawing die and the box is discribed by thermal expansion of die and box.

The main objective of this paper is to discuss a platform which can provide accurate information to moving objects like a car in poor environmental conditions where the use of signals of GPS is not possible. This approach is going to integrate imaging sensor data into an inertial navigation system. Navigation systems are getting smart and accurate but still, an error occurs at long distances causing a failure to find out accurate location. In order to increase the accuracy front camera in a car is proposed as a sensor for the navigation system. Before this problem is solved with the help of extended Kalmanfilter but still, the small error occurs. In order to find out, accurate location landmarks will be detected from the real-time environment and will be matched with the landmarks which are already stored database. Detection is the challenge in an open environment in which object must be illumination invariant, pose invariant and scale invariant. Selection between algorithms according to the requirement is important. SIFT is a feature descriptor which creates the description of features in an image and known as the more accurate algorithm. Speeded up robust features (SURF) is another algorithm in computer considered as fast and less accurate than SIFT. Most of the time it is not a problem with given algorithms but the feature is not detected or matched because of illumination, scale, and pose. In this condition use of filters and other techniques is important for better results. Better results mean required information from images must extract easily, this part is obtained with the help of computer vision and image processing. After creating matched images data, this data is given to navigation data calculation so that it can produce an exact location based on matched images and time calculation. Navigation data calculation unit has the connection with Landmark Database so navigation system can compute that at this point landmark is present and it is matched and assure that given location is accurate. In this way accuracy, safety and security can be assured.

Light detection and ranging (lidar) is used for various applications such as remote sensing, altimetry and imaging. In this talk, a linearly chirped pulse source is introduced that generates wavelength-swept pulses exhibiting ~6 nm optical bandwidth with > 20 km coherence length. The chirped pulses are used in an interferometric lidar setup to perform distance measurements with sub-millimeter resolution (using pulses that are a few meters long), at target distances > 10 km, with at least 25 dB signal-to-noise ratio at the receiver. A pulse repetition rate of 20 MHz provides fast update rates, while chirped pulse amplification allows easy amplification of optical signals to high power levels that are required for long range operation. A pulse tagging scheme based on phase modulation is used to demonstrate unambiguous, long range measurements. In addition to this, simultaneous measurement of target range and Doppler velocity is performed using a target moving at a speed of over 330 km/h (205 mph) inside the laboratory. In addition to this, spectral phase modulation of the chirped pulses is demonstrated to compensate for the undesirable ripple in the group delay of the chirped pulses. Moreover, spectral amplitude modulation is used to generate pulses with Gaussian temporal intensity profiles and a two-fold increase in the lidar range resolution (284 um) is observed.

À la fin des années 90, deux équipes indépendantes ont montré l’expansion accélérée de notre Univers, à partir des mesures de distances de supernovas de type Ia (SNIa). Depuis, une des priorités de la cosmologie moderne est de caractériser ce phénomène et d’en comprendre ses fondements. L’amélioration des mesures de distance réalisées à partir des SNIa est une technique majeure permettant de mieux caractériser l’accélération et donc de déterminer la nature physique de ce phénomène. Ce document développe un nouveau modèle de distribution spectrale en énergie de SNIa nommé le Supernova Useful Generator And Reconstructor (SUGAR) permettant d’améliorer les mesures des distances. Ce modèle est construit à partir des propriétés spectrales des SNIa et des données spectrophotométriques de la collaboration The Nearby Supernova Factory. L’avancée principale, proposée dans SUGAR, réside dans l’ajout de deux paramètres supplémentaires pour caractériser la variabilité des SNIa. Le premier dépend des propriétés des vitesses des éjectas des SNIa, le deuxième dépend de leurs raies du calcium. L’ajout de ces paramètres, ainsi que la grande qualité des données de la collaboration the Nearby Supernova Factory font de SUGAR le meilleur modèle qui existe pour décrire la distribution spectrale en énergie des SNIa et améliore les mesures des distances de l’ordre de 15% par rapport à la méthode usuelle. Les performances de ce modèle en font un excellent candidat pour préparer les expériences futures comme LSST ou WFIRST. Par ailleurs, ce document présente une analyse sur l’effet de l’appartenance d’une SNIa à un amas de galaxies sur sa mesure de distance. Les galaxies d’un amas possèdent une vitesse propre largement supérieure à la valeur supposée lors de la mesure des distances avec les SNIa. Ceci a pour conséquence d’introduire une source d’erreur systématique sur la mesure de distance. Le fait de ne pas prendre en compte cet effet peut dégrader la mesure de distance de l’ordre de 2,5% pour les SNIa appartenant à un amas. Cette analyse à été réalisée en utilisant les données de la collaboration the Nearby Supernova Factory et des catalogues public d’amas de galaxies. / At the end of the 90s, two independent teams showed, based on distance measurements of type Ia supernovæ (SNIa), that expansion of our Universe is accelerating. Since then, one of the priorities of modern cosmology is to characterize this phenomenon and to understand its nature. The improvement of distance measurements of SNIa is one technique to improve the constraints on acceleration and to determine the physical nature of it. This document develops a new SNIa spectral energy distribution model, called the Supernova Useful Generator and Reconstructor (SUGAR), which improves distance measurement. This model is constructed from SNIa spectral properties and spectrophotometric data from The Nearby Supernova Factory collaboration. The main advancement proposed in SUGAR is the addition of two additional parameters to characterize the SNIa variability. The first depends on the properties of SNIa ejecta velocity, the second depends on their calcium lines. The addition of these parameters as well as the high quality of the data of The Nearby Supernova Factory collaboration make SUGAR the best model available to describe the spectral energy distribution of SNIa and improves distances measurements of the order of 15 % relative to the usual method. The performance of this model makes it an excellent candidate for preparing future experiments like LSST or WFIRST. In addition, this document presents an analysis of the effect of SNIa belonging to a galaxy cluster on its distance measurement. Galaxies of a cluster have a peculiar velocity much higher than the assumed value when measuring distances with SNIa. This has the effect of introducing a systematic error into the distance measurement. Failure to take into account this effect may degrade the distance measurement by 2.5% for SNIa belonging to a cluster. This analysis was carried out using data from the collaboration of the Nearby Supernova Factory and public catalogs of galaxy cluster.

This thesis deals with optical distance measurement and 3D scene measurement using focusing techniques with focus on confocal microscopy, depth from focus and depth from defocus. Theoretical part of the thesis is about different approaches to depth map generation and also about micro image defocusing technique for measuring refractive index of transparent materials. Then the camera calibration for focused techniques is described. In the next part of the thesis is described experimentally verification of depth from focus and depth from defocus techniques. For the first technique are shown results of depth map generation and for the second technique is shown comparison between measured distance values and real distance values. Finally, the discussed techniques are compared and evaluated.

This thesis describes application of image processing for precise distance measurement in self acting production of a tip for AFM microscopes. The main goal is to measure distances between assembly parts during fabrication process. The purpose is to acquire a data for self acting assembly line which have to substitute inaccurate and nonrecurring manual assembly process. The assembly process consists of three technological steps. In first two steps the tungsten wire is glued to the cantilever. Distance measurement is necessary in all axes for proper alignment of parts. In third step the sharp tip is etched by KOH solution. The right distance between liquid level and the cantilever must be kept. A camera with high resolution and macro objective is used to acquire an image. Camera image is then calibrated to suppress distortions and scene position with respect to camera position. Length conversion coefficient is also computed. Object recognition and distance measurement is based on standard computer vision methods, mainly: adaptive thresholding, moments, image statistics, canny edge detector, Hough transform… Proposed algorithms have been implemented in C++ using Intel OpenCV library. The final achieved distance resolution is about 10µm per pixel. Algorithm output was successfully used to assembly few test tips.

My thesis deals with the construction of on-board computers for a motorcycle. The scheme is based on the parameters of onboard computers appearing on the market. In comparison with the models, which are offered commercially it also allows measurement of the motorcycle’s fuel consumption and location by using GPS. On-board computer measures speed, traveled distance, motor speed and engine temperature. It is controlled by a pair of eight-bit AVR microcontrollers. The measured data are showed by a graphical LCD display with touch screen.