Les travaux de cette thèse concernent la détection des changements dans des séries chronologiques de photographies de paysages prises depuis le sol. Ce contexte de comparaison d'images successives est celui que rencontrent les géographes de l'environnement qui ont recours aux observatoires photographiques du paysage. Ces outils d'analyse et d'aide à la décision sont des bases de données de photographies constituées selon une méthodologie stricte de rephotographie de la même scène, à des pas de temps réguliers. Le nombre de clichés est parfois très important, et l'analyse humaine fastidieuse et relativement imprécise, aussi un outil automatisant la comparaison de photos de paysage deux à deux pour mettre en évidence les changements serait une aide considérable dans l'exploitation des observatoires photographiques du paysage. Bien entendu, les variations dans l'éclairement, la saisonnalité, l'heure du jour, produisent fatalement des clichés entièrement différents à l'échelle du pixel. Notre objectif était donc de concevoir un système robuste face à ces changements mineurs, mais capable de détecter les changements pertinents de l'environnement. De nombreux travaux autour de la détection des changements ont été effectués pour des images provenant de satellites. Mais l'utilisation d'appareils photographiques numériques classiques depuis le sol pose des problèmes spécifiques comme la limitation du nombre de bandes spectrales et la forte variation de profondeur dans une même image qui induit des apparences différentes des mêmes catégories d'objets en fonction de leurs positions dans la scène. Dans un premier temps, nous avons exploré la voie de la détection automatique des changements. Nous avons proposé une méthode reposant sur le recalage et la sur-segmentation des images en superpixels. Ces derniers sont ensuite décrits par leur niveau de gris moyen ainsi que par leur texture au travers d'une représentation sous la forme d'histogrammes de textons. La distance de Mahalanobis entre ces descripteurs permet de comparer les superpixels correspondants entre deux images prises à des dates différentes. Nous avons évalué les performances de cette approche sur des images de l'observatoire photographique du paysage constitué lors de la construction de l'autoroute A89. Parmi les méthodes de segmentation utilisées pour produire les superpixels, les expérimentations que nous avons menées ont mis en évidence le bon comportement de la méthode de segmentation d'Achanta. La pertinence d'un changement étant fortement liée à l'application visée, nous avons exploré dans un second temps une piste faisant intervenir l'utilisateur. Nous avons proposé une méthode interactive de détection des changements reposant sur une phase d'apprentissage. Afin de détecter les changements entre deux images, l'utilisateur désigne, grâce à un outil de sélection, des échantillons constitués d'ensembles de pixels correspondant à des zones de changement et à des zones d'absence de changement. Chaque couple de pixels correspondants, c'est-à-dire situés au même endroit dans les deux images, est décrit par un vecteur de 16 valeurs principalement calculées à partir de l'image des dissemblances. Cette dernière est obtenue en mesurant, pour chaque couple de pixels correspondants, la dissemblance des niveaux de gris de leurs voisinages. Les échantillons désignés par l'utilisateur permettent de constituer des données d'apprentissage qui sont utilisées pour entraîner un classifieur. Parmi les méthodes de classification évaluées, les résultats expérimentaux montrent que les forêts d'arbres décisionnels donnent les meilleurs résultats sur les séries photographiques que nous avons utilisées. / This work deals with change detection from chronological series of photographs acquired from the ground. This context of consecutive images comparison is the one encountered in the field of integrated geography where photographic landscape observatories are widely used. These tools for analysis and decision-making consist of databases of photographic images obtained by strictly rephotographing the same scene at regular time intervals. With a large number of images, the human analysis is tedious and inaccurate. So a tool for automatically comparing pairs of landscape photographs in order to highlight changes would be a great help for exploiting photographic landscape observatories. Obviously, lighting variations, seasonality, time of day induce completely different images at the pixel level. Our goal is to design a system which would be robust to these insignificant changes and able to detect relevant changes of the scene. Numerous studies have been conducted on change detection from satellite images. But the utilization of classic digital cameras from the ground raise some specific problems like the limitation of the spectral band number and the strong variation of the depth in a same image which induces various appearance of the same object categories depending on their position in the scene. In the first part of our work, we investigate the track of automatic change detection. We propose a method lying on the registration and the over-segmentation of the images into superpixels. Then we describe each superpixel by its texture using texton histogram and its gray-level mean. A distance measure, such as Mahalanobis distance, allows to compare corresponding superpixels between two images acquired at different dates. We evaluate the performance of the proposed approach on images taken from the photographic landscape observatory produced during the construction of the French A89 highway. Among the image segmentation methods we have tested for superpixel extraction, our experiments show the relatively good behavior of Achanta segmentation method. The relevance of a change is strongly related to the intended application, we thus investigate a second track involving a user intervention. We propose an interactive change detection method based on a learning step. In order to detect changes between two images, the user designates with a selection tool some samples consisting of pixel sets in "changed" and "unchanged" areas. Each corresponding pixel pair, i.e., located at the same coordinates in the two images, is described by a 16-dimensional feature vector mainly calculated from the dissimilarity image. The latter is computed by measuring, for each corresponding pixel pair, the dissimilarity of the gray-levels of the neighbors of the two pixels. Samples selected by the user are used as learning data to train a classifier. Among the classification methods we have tried, experimental results indicate that random forests give the better results for the tested image series.

L’utilisation de techniques informatiques pour la reconnaissance et l'identification des poissons est devenue assez populaire parmi les chercheurs. Ces nouvelles approches sont importantes, puisque les informations extraites sur les poissons telles que leurs trajectoires, leurs positions ou leurs couleurs, permettent de déterminer si les poissons sont en bonne santé ou en état de stress. Les méthodes existantes ne sont pas assez précises notamment lorsque des éléments tels que les bulles ou des zones éclairées peuvent être identifiées comme étant des poissons. De plus, les taux de reconnaissance et d'identification des systèmes existants peuvent encore être améliorés afin d’obtenir des résultats à la fois meilleurs et plus précis. Afin d’obtenir de meilleurs taux de reconnaissance et d'identification, un système amélioré a été construit en combinant plusieurs méthodes de détection et d’analyse. Tout d'abord, la première étape a consisté à proposer une méthode de suivi d'objets dans le but de localiser en temps réel la position des poissons à partir de vidéos. Celle-ci inclut le suivi automatisé multi-cibles de poissons dans un aquarium. Les performances en termes de détection et d’identification risquaient d’être faibles notamment en raison du processus de suivi dans un environnement temps réel. Une méthode de suivi des poissons plus précise est donc proposée ainsi qu'une méthode complète pour identifier et détecter les modèles de nage des poissons. Dans ces travaux, nous proposons, pour le suivi des poissons, une amélioration de l’algorithme du filtre particulaire en l’associant à un algorithme de détection de mouvement. Un système doté de deux caméras est également proposé afin d'obtenir un meilleur taux de détection. La seconde étape comprend la conception et le développement d'une méthode améliorée pour le recadrage et la segmentation dynamique des images dans un environnement temps réel. Ce procédé est proposé pour extraire de la vidéo les images représentant les poissons en éliminant les éléments provenant de l’arrière-plan. La troisième étape consiste à caractériser les objets (les poissons). La méthode proposée est basée sur des descripteurs utilisant la couleur pour caractériser les poissons. Ces descripteurs sont ensuite utilisés dans la suite des traitements. Dans nos travaux, les descripteurs couleurs généralisés de Fourier (GCFD : Generalized Color Fourier Descriptor) sont utilisés et une adaptation basée sur la détection de l’environnement est proposée afin d’obtenir une identification plus précise des poissons. Une méthode de mise en correspondance basée sur un calcul de distance est utilisée pour comparer les vecteurs de caractéristiques des images segmentées afin de classifier les poissons présents dans la vidéo. Un prototype dont le but est de modéliser les profils de nage des poissons a été développé. Celui-ci intègre toutes les méthodes proposées et a permis d’évaluer la validité de notre approche. Les résultats montrent que les méthodes proposées améliorent la reconnaissance et l’identification en temps réel des poissons. La méthode de suivi proposée montre une amélioration par rapport au procédé basé sur le filtre particulaire classique. Le recadrage dynamique et la méthode de segmentation temps-réel présentent en termes de précision un pourcentage moyen de 84,71%. La méthode de caractérisation des objets développée pour reconnaitre et identifier en temps réel les poissons montre également une amélioration par rapport aux descripteurs couleurs classiques. Le travail réalisé peut trouver une application directe auprès des aquaculteurs afin de suivre en temps réel et de manière automatique le comportement des poissons et éviter ainsi un suivi « visuel » tel qu’il est réalisé actuellement. / Recognition and identification of fish using computational methods have increasingly become a popular research endeavour among researchers. The methods are important as the information displayed by the fish such as trajectory patterns, location and colour could determine whether the fish are healthy or under stress. Current methods are not accurate especially when there exist thresholds such as bubbles and some lighted areas which might be identified as fish. Besides, the recognition and identification rate of the existing systems can still be improved to obtain better and more accurate results. In order to achieve a better recognition and identification rate, an improved scheme consisting of a combination of several methods is constructed. First of all, the first approach is to propose an object tracking method for the purpose of locating the position of fish for real-time videos. This includes the consideration of tracking multiple fish in a single tank in an automated way. The detection and identification rate may be slow due to the on-going tracking process especially in a real-time environment. A more accurate fish tracking method is proposed as well as a systematic method to identify and detect fish swimming patterns. In this research, the particle filter algorithm is enhanced and further combined with the motion detection algorithm for fish tracking. A dual camera system is also proposed to obtain better detection rate. The second approach includes the design and development of an enhanced method for dynamically cropping and segmenting images in real-time environment. This method is proposed to extract each image of the fish from every successive video frame to reduce the tendency of detecting the background as an object. The third approach includes an adapted object characterisation method which utilises colour feature descriptors to represent the fish in a computational form for further processing. In this study, an object characterisation method, GCFD (Generalized Colour Fourier Descriptor) is adapted to suit the environment for more accurate identification of the fish. A feature matching method based on distance matching is used to match the feature vectors of the segmented images for classifying the specific fish in the recorded video. In addition, a real-time prototype system which models the fish swimming pattern incorporating all the proposed methods is developed to evaluate the methods proposed in this study. Based on the results, the proposed methods show improvements which result in a better real-time fish recognition and identification system. The proposed object tracking method shows improvement over the original particle filter method. Based on the average percentage in terms of the accuracy for the dynamic cropping and segmentation method in real time, an acceptable value of 84.71% was recorded. The object characterisation method which is adapted for fish recognition and identification in real time shows an improvement over existing colour feature descriptors. As a whole, the main output of this research could be used by aquaculturist to track and monitor fish in the water computationally in real-time instead of manually.

abstract: Recent advances in medical imaging technology have greatly enhanced imaging based diagnosis which requires computational effective and accurate algorithms to process the images (e.g., measure the objects) for quantitative assessment. In this dissertation, one type of imaging objects is of interest: small blobs. Example small blob objects are cells in histopathology images, small breast lesions in ultrasound images, glomeruli in kidney MR images etc. This problem is particularly challenging because the small blobs often have inhomogeneous intensity distribution and indistinct boundary against the background. This research develops a generalized four-phased system for small blob detections. The system includes (1) raw image transformation, (2) Hessian pre-segmentation, (3) feature extraction and (4) unsupervised clustering for post-pruning. First, detecting blobs from 2D images is studied where a Hessian-based Laplacian of Gaussian (HLoG) detector is proposed. Using the scale space theory as foundation, the image is smoothed via LoG. Hessian analysis is then launched to identify the single optimal scale based on which a pre-segmentation is conducted. Novel Regional features are extracted from pre-segmented blob candidates and fed to Variational Bayesian Gaussian Mixture Models (VBGMM) for post pruning. Sixteen cell histology images and two hundred cell fluorescent images are tested to demonstrate the performances of HLoG. Next, as an extension, Hessian-based Difference of Gaussians (HDoG) is proposed which is capable to identify the small blobs from 3D images. Specifically, kidney glomeruli segmentation from 3D MRI (6 rats, 3 humans) is investigated. The experimental results show that HDoG has the potential to automatically detect glomeruli, enabling new measurements of renal microstructures and pathology in preclinical and clinical studies. Realizing the computation time is a key factor impacting the clinical adoption, the last phase of this research is to investigate the data reduction technique for VBGMM in HDoG to handle large-scale datasets. A new coreset algorithm is developed for variational Bayesian mixture models. Using the same MRI dataset, it is observed that the four-phased system with coreset-VBGMM has similar performance as using the full dataset but about 20 times faster. / Dissertation/Thesis / Doctoral Dissertation Industrial Engineering 2015

Submitted by Lucas Alexandre Ramos null (magrelolukas@hotmail.com) on 2016-09-12T11:55:17Z No. of bitstreams: 1 Monografia_Final.pdf: 4956502 bytes, checksum: b3c792e3df597c4fabe2093c7ea8b357 (MD5) / Approved for entry into archive by Felipe Augusto Arakaki (arakaki@reitoria.unesp.br) on 2016-09-14T17:56:52Z (GMT) No. of bitstreams: 1 ramos_la_me_bauru.pdf: 4956502 bytes, checksum: b3c792e3df597c4fabe2093c7ea8b357 (MD5) / Made available in DSpace on 2016-09-14T17:56:52Z (GMT). No. of bitstreams: 1 ramos_la_me_bauru.pdf: 4956502 bytes, checksum: b3c792e3df597c4fabe2093c7ea8b357 (MD5) Previous issue date: 2016-08-12 / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / Atualmente, dada a difusão dos computadores, a tarefa de se reconhecer padrões visuais está sendo cada vez mais automatizada, em especial para tratar a vasta e crescente quantidade de imagens digitais existentes. Aplicações de diversas áreas como biometria, recuperação de imagens baseada em conteúdo e diagnóstico médico, se valem do processamento de imagens, bem como de técnicas de extração e análise de características das mesmas, a fim de identificar pessoas, objetos, gestos, textos, etc. As características básicas que são utilizadas para a análise de imagens são: cor, textura e forma. Recentemente, foi proposto um novo descritor de formas denominado HTS (Hough Transform Statistics), o qual se baseia no espaço de Hough para representar e reconhecer objetos em imagens por suas formas. Os resultados obtidos pelo HTS sobre bases de imagens públicas têm mostrado que este novo descritor, além de apresentar altas taxas de acurácia, melhores do que muitos descritores tradicionais propostos na literatura, é rápido, pois tem um algoritmo de complexidade linear. O objetivo deste trabalho foi explorar as possibilidades de representação multiescala do HTS e, assim, propor novos descritores de formas. Escala é um parâmetro essencial em Visão Computacional e a teoria de espaço-escala refere-se ao espaço formado quando se observa, simultaneamente, os aspectos espaciais de uma imagem em várias escalas, sendo a escala a terceira dimensão. Os novos métodos multiescala propostos foram avaliados sobre várias bases de dados e seus desempenhos foram comparados com o desempenho do HTS e com os principais descritores de formas encontrados na literatura. Resultados experimentais mostraram que os novos descritores propostos neste trabalho são mais rápidos e em alguns casos também mais precisos. / Currently, given the widespread of computers through society, the task of recognizing visual patterns is being more and more automated, in particular to treat the large and growing amount of digital images available. Applications in many areas, such as biometrics, content-based image retrieval, and medical diagnostic, make use of image processing, as well as techniques for the extraction and analysis of their characteristics, in order to identify persons, objects, gestures, texts, etc. The basic features that are used for image analysis are: color, texture and shape. Recently, it was proposed a new shape descriptor called HTS (Hough Transform Statistics), which is based on the Hough space to represent and recognize objects in images by their shapes. The results obtained by HTS on public image databases have shown that this new shape descriptor, besides showing high accuracy levels, better than many traditional shape descriptors proposed in the literature, is fast, since it has an algorithm of linear complexity. In this dissertation we explored the possibilities of a multiscale and scale-space representation of this new shape descriptor. Scale is a key parameter in Computer Vision and the theory of scale-space refers to the space formed when observing, simultaneously, special aspects of an image at several scales, being the scale the third dimension. The multiscale HTS methods were evaluated on the same databases and their performances were compared with the main shape descriptors found in the literature and with the monoscale HTS. Experimental results showed that these new descriptors are faster and can also be more accurate in some cases. / FAPESP: 2014/10611-0

Made available in DSpace on 2016-12-08T16:19:06Z (GMT). No. of bitstreams: 1 amandaAV.pdf: 1956955 bytes, checksum: 726c769bb22d75ff984a0d82b74e2f67 (MD5) Previous issue date: 2010-07-10 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / This study investigates the effects of meaning related to estrangement that can lead to images being considered grotesque. the project began by identifying authors who have dealt with the theme of the grotesque within different theoretical frameworks and at different times and went on to study the principles and concepts of discursive semiotics, with the objective of organizing sources of meaning creation. four images by different authors were chosen in order to define a corpus for analysis. these were a scene from the film el laberinto del fauno , by guillermo del toro - 2006; a painting by the canadian marianna gartner, entitled diablo baby iii - 2006; a digital photograph by the north-american maggie taylor, entitled girl in a bee dress 2004, which was used in the opening to the 2005 tv series ghost whisperer , and a scene from the 2004 video by anna natale o banquete . each image was analyzed using a model proposed by sandra ramalho (1998; 2006). after these analyses had been completed, they were in turn analysed in comparison with each other, seeking to identify intertextual isotopes, within the plane of expression (figurative isotopes) and the plane of content (thematic isotopes). thus, taking the images as the source of data, an attempt was made to identify recurring elements,procedures and/or figures that could be classified as causing estrangement / Esta pesquisa apresenta um estudo acerca de efeitos de sentido de estranhamento, os quais podem fazer com que certas imagens visuais ou audiovisuais possam ser consideradas grotescas. foi feito um levantamento de autores filiados a diversas matrizes teóricas, distanciados no tempo, os quais têm em comum a abordagem do tema denominado grotesco. para sustentar a busca desses efeitos de sentido, foram adotados princípios e conceitos derivados da semiótica discursiva. com o intuito de delimitar um corpus de análise foram escolhidas quatro imagens, de distintos autores, quais sejam: uma cena do filme o labirinto do fauno , de guillermo del toro (2006); uma pintura da canadense marianna gartner, intitulada diablo baby iii (2006); uma fotografia digital da norte-americana maggie taylor, intitulada girl in a bee dress (2004), usada na abertura da série de tv ghost whisperer (2005), e uma cena do vídeo o banquete , de anna natale (2004). foram elaboradas leituras, verbais, escritas, de cada umas destas imagens, usando um modelo proposto por sandra ramalho (1998; 2006). após as leituras, foi feita uma análise comparativa entre elas, na busca de isotopias intertextuais, no plano de expressão (isotopias figurativas) e no plano de conteúdo (isotopias temáticas). por este meio, procurou-se identificar elementos constitutivos, procedimentos relacionais ou figuras recorrentes que pudessem ser classificadas como deflagradoras do efeito de sentido de estranhamento, tendo como fontes de dados, portanto, as imagens estudadas

Resumo: Este projeto de pesquisa teve como objetivo estudar toda evolução que governa o crescimento, distribuição e classificação dos pites em aços inoxidáveis austeníticos ABNT 304 e 310S obtidos no estado como recebido e tratados, submetidos a diferentes tempos de exposição em névoa salina. A originalidade deste trabalho baseou-se no desenvolvimento de uma técnica para caracterização morfológica e da corrosão localizada associando com os aspectos de descrição de formas, tamanho, parâmetros específicos e populacionais. O aço inoxidável 304 apresentou morfologia irregulares > região de transição A> cônicos >hemisféricos > região de transição B, sendo que irregulares e região de transição A em maiores quantidades no sistema. Na liga tratada a cada tempo de exposição, a quantidade de pites é da mesma ordem, ou seja, região de transição A, irregulares, cônicos, hemisféricos, região de transição B, sendo que os pites na região de transição A e irregulares estão presentes em maior quantidades no sistema. O aço inoxidável 310S, como recebido, exibiu a seguinte morfologia: pites hemisféricos > região de transição A > região de transição B > irregulares > cônicos, sendo que os pites estão presentes em maiores quantidades em: hemisféricos e região de transição A. A quantidade de pites na liga tratada a cada tempo de exposição é da mesma ordem: região de transição B > hemisféricos > região de transição A > cônicos >irregulares. O aço inoxidável 304 apresentou maior resistência à corrosão por pite do que o aço inoxidável 310S, e também diferenças na distribuição, classificação e mediana dos tamanhos dos pites, conforme os resultados obtidos na avaliação estatística da superfície e perfis dos mesmos. / Abstract: This research project has had as objective to study all evolution that governs the growth, distribution and classification of pits in ABNT 304 and 310S austenitic stainless steels obtained in the state as receveid and treated, submitted to different times of exposition in saline mist. The originality of this work has been based on the development of a technique for morphologic characterization and of located corrosion associating with the shape description, size specific and population parameters. The 304 stainless steel has presented the following morphology: irregular > transition region A > conic > hemispherical > transition region B, in which irregular and transition region A > are in larger amounts in the system. In the treated alloy at each exposition time, the pits amount is at the same order, in other words, transition region A, irregular, conic, hemispherical, transition region B, in which the pits in the transtion region A and irregular are present in larger amounts in the system. The 310S stainless steel, as receveid, has exhibited the following morphology: hemispherical pits > transition region A > transtion region B > irregular > conic, in which the pits are present in large amounts in: hemispherical pits and transition region A. The pits amount in the treated alloy at each time of exposition has the same order: transition region B > hemispherical > transition region A > conic> irregular. The 304 stainless steel has presented pit corrosion resistance larger than the 310S stainless steel, and also differences in the distribution, classification and pits sizes medium, according to the results obtained in the statistical evaluation of their surface and profiles. / Orientador: Eduardo Norberto Codaro / Coorientador: Luis Rogério de Oliveira Hein / Banca: Roberto Zenhei Nakazato / Banca: Hamilton de Felipe / Banca: Gilberto Luis Jardim Pinto da Silva / Banca: Koshun Iha / Doutor

Orientador: Mauro Hugo Mathias / Co orientador: Mauro Pedro Peres / Banca: José Elias Tomazini / Banca: João Zangrandi Filho / Banca: Francisco Carlos Parquet Bizarria / Banca: Edson Antonio Capello Sousa / Resumo: Este trabalho descreve o desenvolvimento de um sistema de análise de imagens de partículas de desgaste encontradas em óleos lubrificantes de equipamentos industriais. Para tanto, foi utilizado um sistema de aquisição de imagem para capturar imagens de amostras de óleo retidas em membranas de filtro e, também, desenvolvida uma metodologia analítica que faz a classificação quantitativa e qualitativa das partículas, relacionando-as ao modo de desgaste na qual foram geradas. Para a classificação quantitativa utilizou-se a norma ISO 4406 e para a qualitativa, a análise por meio de Redes Neurais Artificiais. O sistema aplicado consiste em uma câmera digital, um microscópio óptico monocular, um sistema de filtragem de óleo e dois programas computacionais desenvolvidos para realização da análise automatizada das imagens das partículas de desgaste obtidas. Foram utilizados óleos minerais de redutores de máquinas industriais no processo de obtenção de amostras. As partículas de desgaste foram analisadas pelo processo de microscopia óptica para obtenção da imagem da amostra relacionada ao desgaste. Os resultados obtidos mostraram que o sistema de análise desenvolvido realiza a classificação individual das partículas, através de Redes Neurais Artificiais, com uma eficiência de até 96%, além de analisar as múltiplas partículas contidas nas amostras, exibindo um relatório de acompanhamento e evolução do desgaste. Os programas computacionais desenvolvidos para essa análise possuem interface gráfica de fácil utilização. Eles podem ser amplamente utilizados no estudo e avaliação das partículas de desgaste obtidas de amostras de óleos industriais em empresas ou em universidades para fins educacionais. O sistema pode ser utilizado para análise de superfícies de metais obtidos pelo processo de metalografia ou na análise de imagens de microorganismos obtidas... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: This paper describes the development of an image analysis system for wear particles found in industrial equipment lubricating oil. Hence, it was utilized an image acquisition system to capture image samples of the oil held in filter membranes. An analytical methodology was also developed to classify the particles quantitatively and qualitatively, relating them to the wear mode where they had been generated. The ISO 4406 standard was applied for quantitative classification and Artificial Neural Networks were used for qualitative classification analysis. The applied system consists of a digital camera, a monocular optical microscope, one oil filtering system and two software programs developed to perform the automated analysis of the acquired wear particles images. Mineral oils of gearbox industrial machines were used in the process of achieving the samples. The wear particles were analyzed by an optical microscopy system, to obtain the sample image related to the wear. The results showed that the analysis system that was developed classifies the individual particles through Artificial Neural Networks with 96% accuracy, in addition to analyzing the multiple particles contained in the samples and generating an evaluation report and wear evolution. The software programs developed for the analysis have a graphical interface easy to use. They can be used in the study and evaluation of the wear particles obtained from industrial oil samples in the companies or in the universities for educational purposes. The system can be applied to analyze the surface of metals acquired by metallographic processes or in the image analysis of microorganisms acquired from blood samples, opening a wide field of application within universities and researches. / Doutor

Orientador: Maria Helena Moraes / Banca: Celia Regina Paes Bueno / Banca: Ana Maria Conte e Castro / Resumo: As propriedades físicas dos solos agricultáveis vêm sofrendo grandes modificações, sendo a compactação apontada como a principal causa destas mudanças em virtude do tráfego máquinas e uso inadequado de equipamentos agrícolas. A compactação ocorre principalmente em solos úmidos, pois a água age como agente lubrificante, melhorando o arranjo entre as partículas. Por isso a importância da adição de matéria orgânica ao solo, já que esta possui um alto poder de adsorção de água, minimizando os efeitos ocasionados pela compactação. O trabalho foi desenvolvido com o objetivo de avaliar a eficiência da utilização de materiais orgânicos em algumas propriedades físicas de um Latossolo Vermelho submetido à compactação, por análises de imagens e de rotina. O experimento foi conduzido em laboratório no Departamento de Recursos Naturais - Ciência do Solo, na Faculdade de Ciências Agronômicas - UNESP, em Botucatu-SP. O delineamento adotado foi o inteiramente casualizado, constituído por 32 tratamentos, em esquema fatorial duplo 4x4, sendo, para cada material orgânico (serragem e BIOMIX®), quatro intensidades de compactação e quatro doses dos materiais (0, 30, 50 e 80 t ha-1), com quatro repetições. Amostras deformadas foram coletadas na camada de 0 a 20 cm de um Latossolo Vermelho distroférrico textura argilosa sob vegetação de mata. A umidade de máxima compactação do solo foi obtida pelo ensaio de Proctor Normal. As amostras de solo foram peneiradas, misturadas às doses dos materiais orgânicos, mantidas em repousou por 30 dias, novamente peneiradas e o conteúdo de água corrigido para 27%. Subamostras foram colocadas em tubos de PVC e compactadas com o auxílio de uma prensa hidráulica, a fim de atingir as intensidades de compactação desejadas. As propriedades físicas avaliadas foram a densidade do solo, a porosidade total... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Compaction is a process that changes negatively the soil physical properties and occurs mainly due to intensive use of machinery and implements for agricultural activities. The addition of organic matter in soil is of great importance to minimize this process by increasing the water demand for the soil reaches the optimum moisture content for compaction. To evaluate the change in physical properties of a soil submitted to compaction, when managed with organic material, an experiment was conducted in the laboratory of the Natural Resources Department - Soil Science, FCA/UNESP, Botucatu-SP, assessed by routine and image analysis. The experimental design was completely randomized design, consisting of 32 treatments in a factorial 4x4 double, and, for each organic material (sawdust and BIOMIX®) four compaction levels and four doses of the materials (0, 30, 50 and 80 t. ha-1), with four replications. Deformed samples were collected from a clayey Oxisol under forest in the layer from 0 to 20 cm. The moisture for maximum soil compaction was obtained using the Standard Proctor test. Soil samples were sieved, mixed with doses of organic materials, incubated for 30 days, sieved again and the water content adjusted to 27%. Sub samples were put in PVC tubes and compressed with the aid of a hydraulic press in order to obtain the desired compaction levels. The physical properties evaluated were soil bulk density, porosity, macroporosity, microporosity, soil penetration resistance and hydraulic 5 conductivity. In addition to the routine method, the evaluation of the compaction effects on macroporosity was done by image analysis acquired from samples after the resin impregnation in the soil samples. The images taken with digital camera were processed in the Visilog 5.4. Statistical analysis was performed using Sisvar version 4.6 (2003), resulting in the analysis of variance and regression test... (Complete abstract click electronic access below) / Mestre

A padronização para a fabricação de instrumentos endodônticos em aço inoxidável contribuiu para o desenvolvimento de novos aspectos geométricos. Surgiram propostas de alterações no desenho da haste helicoidal, da seção reta transversal, da ponta, da conicidade e do diâmetro na extremidade (D0). Concomitantemente, o emprego de ligas em Níquel-Titânio possibilitou a produção de instrumentos acionados a motor, largamente empregados hoje. A cada ano a indústria lança instrumentos com diversas modificações, sem, contudo, disponibilizar informações suficientes quanto às implicações clínicas destas modificações. Existe um crescente interesse no estudo dos diferentes aspectos geométricos e sua precisa metrologia. Tradicionalmente, a aferição de aspectos geométricos de instrumentos endodônticos é realizada visualmente através de microscopia ótica. Entretanto, esse procedimento visual é lento e subjetivo. Este trabalho propõe um novo método para a metrologia de instrumentos endodônticos baseado no microscópio eletrônico de varredura e na análise digital das imagens. A profundidade de campo do MEV permite obter a imagem de todo o relevo do instrumento endodôntico a uma distância de trabalho constante. Além disso, as imagens obtidas pelo detector de elétrons retro-espalhados possuem menos artefatos e sombras, tornando a obtenção e análise das imagens mais fáceis. Adicionalmente a análise das imagens permite formas de mensuração mais eficientes, com maior velocidade e qualidade. Um porta-amostras específico foi adaptado para obtenção das imagens dos instrumentos endodônticos. Ele é composto de um conector elétrico múltiplo com terminais parafusados de 12 pólos com 4 mm de diâmetro, numa base de alumínio coberta por discos de ouro. Os nichos do conector (terminais fêmeas) têm diâmetro apropriado (2,5 mm) para o encaixe dos instrumentos endodônticos. Outrossim, o posicionamento ordenado dos referidos instrumentos no conector elétrico permite a aquisição automatizada das imagens no MEV. Os alvos de ouro produzem, nas imagens de elétrons retro-espalhados, melhor contraste de número atômico entre o fundo em ouro e os instrumentos. No porta-amostras desenvolvido, os discos que compõem o fundo em ouro são na verdade, alvos do aparelho metalizador, comumente encontrados em laboratórios de MEV. Para cada instrumento, imagens de quatro a seis campos adjacentes de 100X de aumento são automaticamente obtidas para cobrir todo o comprimento do instrumento com a magnificação e resolução requeridas (3,12 m/pixel). As imagens obtidas são processadas e analisadas pelos programas Axiovision e KS400. Primeiro elas são dispostas num campo único estendido de cada instrumento por um procedimento de alinhamento semi-automático baseado na inter-relação com o Axiovision. Então a imagem de cada instrumento passa por uma rotina automatizada de análise de imagens no KS400. A rotina segue uma sequência padrão: pré-processamento, segmentação, pós-processamento e mensuração dos aspectos geométricos. / The standardization of stainless steel endodontic instruments has contributed to the development of new geometric features. Many design changes in tip shape, cross section, tapering and diameters have come out. At the same time, the use of Ni-Ti alloys enabled the production of rotary instruments, which are widely employed nowadays. In fact, the industry continuously releases novel instruments with different designs. Nevertheless, not enough information is provided about these modifications and their clinical impacts. Thus, there is a growing interest in the study of these different geometric features and their accurate metrology. Traditionally, the measurement of geometric aspects in endodontic instruments is made visually under an optical microscope. However, this visual procedure is subjective and slow. This work proposes a new method for the metrology of endodontic instruments based on scanning electron microscope (SEM) and digital image analysis. The superior depth of field of the SEM allows the whole relief of an endodontic instrument to be imaged at a constant working distance. Moreover, the images from the back-scattered electrons (BSE) detector have less artifacts and shadows, making the image analysis task easier. In addition, image analysis provides efficient ways of measuring with greater speed and statistical quality. A specific sample holder was adapted for the task of imaging endodontic files. It is composed of a multiple electrical connector, a 12 pole screw terminal strip (4 mm), on an aluminum base covered by gold plates. The holes (female terminals) in the electrical connector have an appropriate diameter (2.5 mm) to fix the endodontic instruments. Besides, the ordered placement of endodontic instruments on the electrical connector allows automating image acquisition in the SEM. The gold plates produce, in BSE images, greater atomic number contrast between the gold background and the instruments. In the built sample holder, the gold plates are in fact gold targets of a sputter coater, because it is a material commonly present in SEM labs. For each file, 4 to 6 adjacent fields at 100X are automatically imaged, to cover its entire length with the required magnification and resolution (3.12 m/pixel). These acquired images are processed and analyzed by AxioVision and KS400 softwares. First, they are assembled in a single extended field image of each instrument by a semi-automated alignment procedure based on cross-correlation in AxioVision. Then, the image of each entire instrument passes through a fully automated image analysis routine in KS400. This routine follows the image analysis standard sequence: pre-processing, segmentation, post-processing and measurement of geometric aspects. The obtained results are consistent with manual measurements but the proposed method is faster. Since assembling 4 to 6 BSE images in an extended field image is the only step that is not fully automated, the proposed method depends much less on the subjectivity of the human operator.

Motion capture is the process of capturing movements from real life into a computer. Existing motion capture systems are often very expensive and require advanced hardware that makes the process complex. This thesis will answer the following question: is it possible to create an optical motion capture system using only a single low cost Dvcamera (Digital Video Camera), that still will produce accurate motion capture data? To answer this question and construct our motion capture system we need to complete these following steps: • Create a usable film sequence. • Analyze the sequence. • Create motion capture data. • Apply the motion capture data for 3D character and analyze the outcome. The method chosen for this thesis is constructive research. In short terms it is the study of whether we can or cannot build a new artifact. The following theoretic tools were used in the process of creating a motion capture system: Color theory, RGB, Connected component labeling, Skeletons in 3D animation, Calculating angels using trigonometry, .x files and Quaternions. We have found that an optical motion capture system is very complex and it is hard to produce as a low budget system. Our attempt did not live up to our expectations. The idea with using only one DV camera was to simplify the system since it would require no calibration or syncronisation. It would also make the system cost efficient and more available to the general public. The single camera solution unfortunatly created a number of problems in our system. Our system does however work with less complex movements. It can produce motion capture data that is accurate enough to be used in low budget games. It is also cost effective compared to other systems on the market. The system has a very easy setup and does not need any calibration in addition to the init position.