Zusammenfassung Heutige Ansätze des 3D-Trackings für die Registrierung in der realen Welt zum Einsatz von Augmented Reality lassen sich in modellbasierte und umgebungsbasierte Verfahren unterteilen. Umgebungsbasierte Verfahren nutzen den SLAM-Algorithmus zur Erzeugung dreidimensionaler Punktwolken der Umgebung in Echtzeit. Modellbasierte Verfahren finden Ihren Ursprung im Canny edge detector und nutzen aus den CAD-Modellen abgeleitete Kantenmodelle. Wird das modellbasierte Verfahren über Kantendetektion und das umgebungsbasierte Verfahren über 3DPunktewolken kombiniert, ergibt sich ein robustes, hybrides 3D-Tracking. Die entsprechenden Algorithmen der verschiedenen Verfahren sind in heute verfügbaren AR-Frameworks bereits implementiert. Der vorliegende Betrag zeigt zwar, welche Effizienz das hybride 3D-Tracking aufweist, jedoch auch die Problematik der erforderlichen geometrischen Ähnlichkeit von idealem CAD-Modell, bzw. Kantenmodell, und realem Objekt. Bei unterschiedlichen Montagestufen an verschiedenen Montagestationen und mit wechselnden Anwendern ist beispielsweise eine erneute Initialisierung erforderlich. Somit bedingt das hybride 3D-Tracking zahlreiche Kantenmodell, die zuvor aus der jeweiligen Montagestufe abgeleitet werden müssen. Hinzu kommen geometrische Abweichungen durch die Fertigung, die je nach Größe der branchenspezifischen Toleranzen keine hinreichend hohe Übereinstimmung mit den abgeleiteten Kantenmodellen aus den idealen CAD-Modellen aufweisen. Die Autoren schlagen daher den Einsatz parametrisch aufgebauter Mastermodelle vor, welche durch eine interaktive Initialisierung geometrisch Instanziiert werden. Zum Einsatz kommt hier ein mobiler Tiefensensor für Smart Devices, welcher mit Hilfe des Anwenders eine Relation der realen geometrischen Merkmale mit den Idealen des CAD-Modells ermöglicht. Des Weiteren wird in dem dargestellten Konzept die Nutzung von speziellen Suchalgorithmen basierend auf geometrischen Ähnlichkeiten vorgeschlagen, sodass eine Registrierung und Instanziierung auch ohne hinterlegtes Mastermodell ermöglicht wird. Der Beitrag fokussiert sich bei der Validierung auf die interaktive Initialisierung anhand eines konkreten anwendungsnahen Beispiels, da die Initialisierung die Grundlage für die weitere Entwicklung des Gesamtkonzeptes darstellt.

UAVs have gained in popularity and the number of applications has soared over the past years, ranging from leisure to commercial activities. This thesis is discussing specifically railroad applications, which is a domain rarely explored. Two different aspects are analysed. While developing a new application or migrating a ground-based system to UAV platform, the different challenges encountered are often unknown. Therefore, this thesis highlights the most important ones to take into consideration during the development process. From a more technical aspect, the implementation of autonomous guidance for UAVs over railroads using vanishing point extraction is studied. Two different algorithms are presented and compared, the first one is using line extraction method whereas the second uses joint activities of Gabor filters. The results demonstrate that the applied methodologies provide good results and that a significant difference exists between both algorithms in terms of computation time. A second implementation tackling the detection of railway topologies to enable the use on multiple rail road configurations is discussed. A first technique is presented using exclusively vanishing points for the detection, however, the results for complex images are not satisfactory. Therefore, a second method is studied using line characteristics on top of the previous algorithm. This second implementation has proven to give good results.

Polarimetric Synthetic Aperture Radar (PolSAR) has been used for various remote sensing applications since more information could be obtained in multiple polarizations. The overall objective of this thesis is to investigate urban area information extraction from PolSAR data with the following specific objectives: (1) to exploit polarimetric scattering model-based decomposition methods for urban areas, (2) to investigate effective methods for man-made target detection, (3) to develop edge detection and superpixel generation methods, and (4) to investigate urban area classification and segmentation. Paper 1 proposes a new scattering coherency matrix to model the cross-polarized scattering component from urban areas, which adaptively considers the polarization orientation angles of buildings. Thus, the HV scattering components from forests and oriented urban areas can be modelled respectively. Paper 2 presents two urban area decompositions using this scattering model. After the decomposition, urban scattering components can be effectively extracted. Paper 3 presents an improved man-made target detection method for PolSAR data based on nonstationarity and asymmetry. Reflection asymmetry was incorporate into the azimuth nonstationarity extraction method to improve the man-made target detection accuracy, i.e., removing the natural areas and detecting the small targets. In Paper 4, the edge detection of PolSAR data was investigated using SIRV model and Gauss-shaped filter. This detector can locate the edge pixels accurately with fewer omissions. This could be useful for speckle noise reduction, superpixel generation and others. Paper 5 investigates an unsupervised classification method for PolSAR data in urban areas. The ortho and oriented buildings can be discriminated very well. Paper 6 proposes an adaptive superpixel generation method for PolSAR images. The algorithm produces compact superpixels that can well adhere to image boundaries in both natural and urban areas. / Polarimetriska Synthetic Aperture Radar (PolSAR) har använts för olika fjärranalystillämpningar för, eftersom mer information kan erhållas från multipolarisad data. Det övergripande syftet med denna avhandling är att undersöka informationshämtning över urbana områden från PolSAR data med följande särskilda mål: (1) att utnyttja polarimetrisk spridningsmodellbaserade nedbrytningsmetoder för stadsområden, (2) att undersöka effektiva metoder för upptäckt av konstgjorda objekt, (3) att utveckla metoder som kantavkänning och superpixel generation, och (4) för att undersöka klassificering och segmentering av stadsområden. Artikel 1 föreslår en ny spridnings-koherens matris för att modellera korspolariserade spridningskomponent från tätorter, som adaptivt utvärderar polariseringsorienteringsvinkel av byggnader. Artikel 2 presenterar nedbrytningstekniken över två urbana områden med hjälp av denna spridningsmodell. Efter nedbrytningen kunde urbana spridningskomponenter effektivt extraheras. Artikel 3 presenterar en förbättrad detekteringsmetod för konstgjorda mål med PolSAR data baserade på icke-stationaritet och asymmetri. integrerades reflektionsasymmetri i icke-stationaritetsmetoden för att förbättra noggrannheten i upptäckten av konstgjorda föremål, dvs. att ta bort naturområden och upptäcka de små föremålen. I artikel 4 undersöktes kantdetektering av PolSAR data med hjälp av SIRV modell och ett Gauss-formad filter. Denna detektor kan hitta kantpixlarna noggrant med mindre utelämnande. Detta skulle den vara användbar för reduktion av brus, superpixel generation och andra. Artikel 5 utforskar en oövervakad klassificeringsmetod av PolSAR data över stadsområden. Orto- och orienterade byggnader kan särskiljas mycket väl. Baserat på artikel 4 föreslår artikel 6 en adaptiv superpixel generationensmetod för PolSAR data. Algoritmen producerar kompakta superpixels som kan kommer att följa bildgränser i både naturliga och stadsområden. / <p>QC 20160607</p>

With the growth of computer power, Digital Image Processing plays a more and more important role in the modern world, including the field of industry, medical, communications, spaceflight technology etc. There is no clear definition how to divide the digital image processing, but normally, digital image processing includes three main steps: low-level, mid-level and highlevel processing. Low-level processing involves primitive operations, such as: image preprocessing to reduce the noise, contrast enhancement, and image sharpening. Mid-level processing on images involves tasks such as segmentation (partitioning an image into regions or objects), description of those objects to reduce them to a form suitable for computer processing, and classification (recognition) of individual objects. Finally, higher-level processing involves &quot;making sense&quot; of an ensemble of recognised objects, as in image analysis. Based on the theory just described in the last paragraph, this thesis is organised in three parts: Colour Edge and Face Detection; Hand motion detection; Hand Gesture Detection and Medical Image Processing. II In Colour Edge Detection, two new images G-image and R-image are built through colour space transform, after that, the two edges extracted from G-image and R-image respectively are combined to obtain the final new edge. In Face Detection, a skin model is built first, then the boundary condition of this skin model can be extracted to cover almost all of the skin pixels. After skin detection, the knowledge about size, size ratio, locations of ears and mouth is used to recognise the face in the skin regions. In Hand Motion Detection, frame differe is compared with an automatically chosen threshold in order to identify the moving object. For some special situations, with slow or smooth object motion, the background modelling and frame differencing are combined in order to improve the performance. In Hand Gesture Recognition, 3 features of every testing image are input to Gaussian Mixture Model (GMM), and then the Expectation Maximization algorithm (EM)is used to compare the GMM from testing images and GMM from training images in order to classify the results. In Medical Image Processing (mammograms), the Artificial Neural Network (ANN) and clustering rule are applied to choose the feature. Two classifier, ANN and Support Vector Machine (SVM), have been applied to classify the results, in this processing, the balance learning theory and optimized decision has been developed are applied to improve the performance.

Este trabalho desenvolveu um novo método para a detecção de contornos em imagens digitais que apresentam objetos de interesse muito próximos e que contêm complexidades associadas ao fundo da imagem como variação abrupta de intensidade e oscilação de iluminação. O método desenvolvido utiliza lógicafuzzy e desvio padrão da declividade (Desvio padrão da declividade fuzzy - FuzDec) para o processamento de imagens e detecção de contorno. A detecção de contornos é uma tarefa importante para estimar características de escoamento bifásico através da segmentação da imagem das bolhas para obtenção de parâmetros como a fração de vazio e diâmetro de bolhas. FuzDec foi aplicado em imagens de instabilidades de circulação natural adquiridas experimentalmente. A aquisição das imagens foi feita utilizando o Circuito de Circulação Natural (CCN) do Instituto de Pesquisas Energéticas e Nucleares (IPEN). Este circuito é completamente constituído de tubos de vidro, o que permite a visualização e imageamento do escoamento monofásico e bifásico nos ciclos de circulação natural sob baixa pressão.Os resultados mostraram que o detector proposto conseguiu melhorar a identificação do contorno eficientemente em comparação aos detectores de contorno clássicos, sem a necessidade de fazer uso de algoritmos de suavização e sem intervenção humana. / This work has developed a new method for digital image contour detection which can be successfully applied to images presenting objects of interest with high proximity and presenting complexities related with background abrupt intensity fluctuations. The developed method makes use of fuzzy logic and declivity standard deviation (Fuzzy Declivity Standard Deviation FuzDec) to image processing and contour detection. Contour detection is an important task to estimate two-phase flow features through bubble segmentation in order to obtain parameters as void fraction and bubble diameter. FuzDec was applied to natural circulation instability images which were experimentally acquired. Image acquisition was done at the Natural Circulation Circuit (CCN) of the Instituto de Pesquisas Energéticas e Nucleares (IPEN) in Brazil. This facility is all made up with glass tubes allowing easy visualization and imaging of one-phase and two-phase flow patterns during natural circulation cycles under low pressures. Results confirm that the proposed detector can improve contour identification when compared to classical contour detector algorithms, without using smoothing algorithms or human intervention.

Granulometria é o processo usado para medir objetos de diferentes tamanhos em imagens de material granular. Frequentemente algoritmos baseados em morfologia matemática ou detecção de arestas são utilizados para esta finalidade. Propomos uma nova abordagem para a granulometria utilizando correlações cruzadas com círculos de tamanhos diferentes. Esta técnica é primeiramente adequada para a detecção de objetos de formato circular, mas pode ser estendido para outras formas utilizando outros núcleos (kernels) de correlação. Experimentos mostram que o novo algoritmo é robusto ao ruído e pode detectar objetos com pouco contraste e/ou com sobreposição parcial. Este trabalho também apresenta características quantitativas estruturais da camada de silício poroso, obtidas aplicando o algoritmo proposto em imagens de microscopia eletrônica de varredura (MEV). O novo algoritmo, que chamamos Granul, calcula as áreas e frequências dos poros. Processamentos adicionais utilizando outros algoritmos classificam os poros em circulares ou quadrados. Relacionamos os resultados quantitativos obtidos com o processo de fabricação e discutimos o mecanismo de formação do poro quadrado no silício. O novo algoritmo mostrou-se confiável no processamento de imagens de MEV e é uma ferramenta promissora para controle no processo de formação dos poros. / Granulometry is the process of measuring the size distribution of objects in an image of granular material. Usually, algorithms based on mathematical morphology or edge detection are used for this task. We propose a entirely new approach for the granulometry using the cross correlations with circles of different sizes. This technique is primarily adequate for detecting circular shaped objects, but it can be extended to other shapes using other correlation kernels. Experiments show that the new algorithm is greatly robust to noise and can detect even faint objects and/or objects with partial superposition. This paper also reports the quantitative structural characteristics of the porous silicon layer based on the proposed algorithm applied to Scanning Electron Microscopy (SEM) images. The new algorithm, that we call Granul, computes the size distribution of pores and classifies the pores in circular or square ones. We relate these quantitative results to the fabrication process and discuss the square porous silicon formation mechanism. The new algorithm shows to be reliable in SEM images processing and is a promising tool to control the pores formation process.

Este trabalho desenvolveu um novo método para a detecção de contornos em imagens digitais que apresentam objetos de interesse muito próximos e que contêm complexidades associadas ao fundo da imagem como variação abrupta de intensidade e oscilação de iluminação. O método desenvolvido utiliza lógicafuzzy e desvio padrão da declividade (Desvio padrão da declividade fuzzy - FuzDec) para o processamento de imagens e detecção de contorno. A detecção de contornos é uma tarefa importante para estimar características de escoamento bifásico através da segmentação da imagem das bolhas para obtenção de parâmetros como a fração de vazio e diâmetro de bolhas. FuzDec foi aplicado em imagens de instabilidades de circulação natural adquiridas experimentalmente. A aquisição das imagens foi feita utilizando o Circuito de Circulação Natural (CCN) do Instituto de Pesquisas Energéticas e Nucleares (IPEN). Este circuito é completamente constituído de tubos de vidro, o que permite a visualização e imageamento do escoamento monofásico e bifásico nos ciclos de circulação natural sob baixa pressão.Os resultados mostraram que o detector proposto conseguiu melhorar a identificação do contorno eficientemente em comparação aos detectores de contorno clássicos, sem a necessidade de fazer uso de algoritmos de suavização e sem intervenção humana. / This work has developed a new method for digital image contour detection which can be successfully applied to images presenting objects of interest with high proximity and presenting complexities related with background abrupt intensity fluctuations. The developed method makes use of fuzzy logic and declivity standard deviation (Fuzzy Declivity Standard Deviation FuzDec) to image processing and contour detection. Contour detection is an important task to estimate two-phase flow features through bubble segmentation in order to obtain parameters as void fraction and bubble diameter. FuzDec was applied to natural circulation instability images which were experimentally acquired. Image acquisition was done at the Natural Circulation Circuit (CCN) of the Instituto de Pesquisas Energéticas e Nucleares (IPEN) in Brazil. This facility is all made up with glass tubes allowing easy visualization and imaging of one-phase and two-phase flow patterns during natural circulation cycles under low pressures. Results confirm that the proposed detector can improve contour identification when compared to classical contour detector algorithms, without using smoothing algorithms or human intervention.

O presente trabalho trata-se do desenvolvimento de um programa para de análise de imagens de topografia corneana de sistemas comerciais, para ser implementado no topógrafo corneano para Lâmpada de Fenda, em desenvolvimento no Laboratório de Instrumentação Oftálmica - EESC/USP e no Laboratório de Física Oftálmica - FMRP/USP. O programa foi desenvolvido em C++, utilizando a plataforma Windows, e fornece mapas axiais de topografia corneana. O programa foi testado em esferas de calibração e em olhos humanos, apresentando um fator de correlação de 0,9998 para as medidas em esferas e um erro inerente estimado em 3%. Os mapas de topografias axiais em olhos humanos foram comparados com os mapas gerados por sistemas comerciais e o padrão visual de forma e relevo estão em concordância. / This work is about a software for the analisys of corneal topography images provided by commercial available systems to be implemented in a corneal topographer for slit lamps under evelopment at Laboratório de Instrumentação Oftálmica . EESC/USP e no Laboratório de Física Oftálmica . FRMP/USP. The software was developed in Borland C++ Builder for Windows and provides the corneal topography axial maps. The software has been tested in calibration spheres and in human eyes, presenting a correlation factor of 0,9998 for the measurements performed in the spheres and an inherent error of 3%. The axial topographic maps form the exams performe in human eyes have been compared to the axial maps provided by the commercial available system and the visual pattern as well as the relief are in accordance.

This thesis proposes a method to reconstruct a frontal facial video basedon encoding done with the facial profile of another video sequence.The reconstructed facial video will have the similar facial expressionchanges as the changes in the profile video. First, the profiles for boththe reference video and for the test video are captured by edge detection.Then, asymmetrical principal component analysis is used to model thecorrespondence between the profile and the frontal face. This allows en-coding from a profile and decoding of the frontal face of another video.Another solution is to use dynamic time warping to match the profilesand select the best matching corresponding frontal face frame for re-construction. With this method, we can reconstructed the test frontalvideo to make it have the similar changing in facial expressions as thereference video. To improve the quality of the result video, Local Lin-ear Embedding is used to give the result video a smoother transitionbetween frames.

In many instances arising prominently, but not exclusively, in imaging problems, it is important to condense the salient information so as to obtain a low-dimensional approximant of the data. This thesis is concerned with two basic situations which call for such a dimension reduction. The first of these is the statistical recovery of smooth edges in regression and density surfaces. The edges are understood to be contiguous curves, although they are allowed to meander almost arbitrarily through the plane, and may even split at a finite number of points to yield an edge graph. A novel locally-parametric nonparametric method is proposed which enjoys the benefit of being relatively easy to implement via a `tracking' approach. These topics are discussed in Chapters 2 and 3, with pertaining background material being given in the Appendix. In Chapter 4 we construct concomitant confidence bands for this estimator, which have asymptotically correct coverage probability. The construction can be likened to only a few existing approaches, and may thus be considered as our main contribution. ¶ Chapter 5 discusses numerical issues pertaining to the edge and confidence band estimators of Chapters 2-4. Connections are drawn to popular topics which originated in the fields of computer vision and signal processing, and which surround edge detection. These connections are exploited so as to obtain greater robustness of the likelihood estimator, such as with the presence of sharp corners. ¶ Chapter 6 addresses a dimension reduction problem for spatial data where the ultimate objective of the analysis is the discrimination of these data into one of a few pre-specified groups. In the dimension reduction step, an instrumental role is played by the recently developed methodology of functional data analysis. Relatively standar non-linear image processing techniques, as well as wavelet shrinkage, are used prior to this step. A case study for remotely-sensed navigation radar data exemplifies the methodology of Chapter 6.