576 research outputs found
2D qualitative shape matching applied to ceramic mosaic assembly
A theory of shape recognition of 2D objects and its application in the ceramic industry for intelligent automation of the mosaic mural assembly process are presented in this paper. This theory qualitatively describes the shapes of the objects, considering: (i) shape boundary characteristics, such as angles, relative length, concavities, and curvature; and (ii) their color and size. The shapes to be recognized may be regular or irregular closed polygons, or closed curvilinear figures. Each figure is described as a symbolic character string that contains all its distinctive characteristics. This description is used to determine whether the shape of two figures matches. Then, given a design of a mosaic and given a set of physical ceramic tesserae, an application is developed in order to recognize the tesserae that form the mosaic, thus enabling the intelligent and automated assembly of ceramic mosaics
Perceiving environmental structure from optical motion
Generally speaking, one of the most important sources of optical information about environmental structure is known to be the deforming optical patterns produced by the movements of the observer (pilot) or environmental objects. As an observer moves through a rigid environment, the projected optical patterns of environmental objects are systematically transformed according to their orientations and positions in 3D space relative to those of the observer. The detailed characteristics of these deforming optical patterns carry information about the 3D structure of the objects and about their locations and orientations relative to those of the observer. The specific geometrical properties of moving images that may constitute visually detected information about the shapes and locations of environmental objects is examined
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Development of novel laser diagnostic techniques for the quantitative study of premixed flames
The main topic of this thesis concerns the development and application of laser diagnostic techniques for accurate temperature measurements and for the determination of flamefront properties in premixed flames that can serve as input data for computational fluid dynamical (CFD) models in technical combustion. The work comprises of a number of related studies, to address problems of relevance in the field of combustion research. The first part of this work involves the development and testing of an improved method for the computation of flamefront curvature in lean premixed turbulent flames. Measurements of spatially resolved heat release rate along the flamefront were then compared with the curvature data and it could be shown that a significant correlation exists between local rate of heat release and flamefront curvature. The results here agree with predictions from CFD models and improve on previous experimental attempts to find a correlation between curvature and heat release. In the second part of this work, the focus was shifted towards the development and application of improved thermometry techniques. One study was on the improvement and application of a coherent anti-Stokes Raman spectroscopy (CARS) setup to an acoustically-forced turbulent lean premixed flame stabilised on a burner, whose design was modelled to mimic phenomena of relevance in industrial combustors. In a related previous study reported in the literature two-line OH planar laser induced fluorescence had been applied to this flame and it was suspected that the results were inaccurate. Using CARS, these inaccuracies could be verified, amounting to discrepancies in temperature of up to 47% compared to the true temperatures. A major effort towards the end of this project was focused on the improvement of traditional thermometry techniques, in order to make them more accurate, faster, and spatially resolved. A technique based on indium two-line atomic fluorescence (TLAF) thermometry was developed and applied, which employed a novel extended cavity diode laser design, and it was shown for the first time that temperature measurements with high accuracy and precision could be performed in low pressure sooting flames without recourse to calibration. Both the high precision and accuracy of the technique allowed for the deduction that the temperature in the flames studied here is relatively insensitive to changes in pressure in stark contrast to the soot volume fraction. Finally, it is shown for the first time that low power diode lasers can be used in combination with indium TLAF to measure spatially and temporally highly resolved temperatures in a quasi-continuous fashion. We demonstrated such measurements at effective rates of 3.5 kHz in a steady laminar test flame yielding an unprecedented precision of 1.5 % at ~2000 K at this measurement rate
Upper airways segmentation using principal curvatures
Esta tesis propone una nueva técnica para segmentar las vías aéreas superiores. Esta propuesta
permite la extracción de estructuras curvilíneas usando curvaturas principales. La propuesta
permite la extracción de éstas estructuras en imágenes 2D y 3D. Entre las principales novedades
se encuentra la propuesta de un nuevo criterio de parada en la propagación del algoritmo de
realce de contraste (operador multi-escala de tipo sombrero alto). De la misma forma, el criterio
de parada propuesto es usado para detener los algoritmos de difusión anisotrópica. Además, un
nuevo criterio es propuesto para seleccionar las curvaturas principales que conforman las
estructuras curvilíneas, que se basa en los criterios propuestos por Steger, Deng et. al. y
Armande et. al. Además, se propone un nuevo algoritmo para realizar la supresión de nomáximos
que permite reducir la presencia de discontinuidades en el borde de las estructuras
curvilíneas. Para extraer los bordes de las estructuras curvilíneas, se utiliza un algoritmo de
enlace que incluye un nuevo criterio de distancia para reducir la aparición de agujeros en la
estructura final. Finalmente, con base en los resultados obtenidos, se utiliza un algoritmo
morfológico para cerrar los agujeros y se aplica un algoritmo de crecimiento de regiones para
obtener la segmentación final de las vías respiratorias superiores.This dissertation proposes a new approach to segment the upper airways. This proposal allows
the extraction of curvilinear structures based on the principal curvatures. The proposal
allows extracting these structures from 2D and 3D images. Among the main novelties is the
proposal of a new stopping criterion to stop the propagation of the contrast enhancement algorithm
(multiscale top-hat morphological operator). In the same way, the proposed stopping
criterion is used to stop the anisotropic diffusion algorithms. In addition, a new criterion is
proposed to select the principal curvatures that make up the curvilinear structures, which is
based on the criteria proposed by Steger, Deng et. al. and Armande et. al. Furthermore, a
new algorithm to perform the non-maximum suppression that allows reducing the presence
of discontinuities in the border of curvilinear structures is proposed. To extract the edges of
the curvilinear structures, a linking algorithm is used that includes a new distance criterion to
reduce the appearance of gaps in the final structure. Finally, based on the obtained results, a
morphological algorithm is used to close the gaps and a region growing algorithm to obtain
the final upper airways segmentation is applied.Doctor en IngenieríaDoctorad
Perception and intelligent localization for autonomous driving
Mestrado em Engenharia de Computadores e TelemáticaVisão por computador e fusão sensorial são temas relativamente recentes, no entanto largamente adoptados no desenvolvimento de robôs autónomos que exigem adaptabilidade ao seu ambiente envolvente. Esta dissertação foca-se numa abordagem a estes dois temas para alcançar percepção no contexto de condução autónoma. O uso de câmaras para atingir este fim é um
processo bastante complexo. Ao contrário dos meios sensoriais clássicos que fornecem sempre o mesmo tipo de informação precisa e atingida de forma determinística, as sucessivas imagens adquiridas por uma câmara estão repletas
da mais variada informação e toda esta ambígua e extremamente difícil de extrair. A utilização de câmaras como meio sensorial em robótica
é o mais próximo que chegamos na semelhança com aquele que é o de maior importância no processo de percepção humana, o sistema de visão. Visão por computador é uma disciplina científica que engloba àreas como: processamento
de sinal, inteligência artificial, matemática, teoria de controlo, neurobiologia e física.
A plataforma de suporte ao estudo desenvolvido no âmbito desta dissertação é o ROTA (RObô Triciclo Autónomo) e todos os elementos que consistem
o seu ambiente. No contexto deste, são descritas abordagens que foram introduzidas com fim de desenvolver soluções para todos os desafios que o
robô enfrenta no seu ambiente: detecção de linhas de estrada e consequente percepção desta, detecção de obstáculos, semáforos, zona da passadeira e zona de obras. É também descrito um sistema de calibração e aplicação da remoção da perspectiva da imagem, desenvolvido de modo a mapear os elementos percepcionados em distâncias reais. Em consequência do sistema
de percepção, é ainda abordado o desenvolvimento de auto-localização integrado
numa arquitectura distribuída incluindo navegação com planeamento inteligente. Todo o trabalho desenvolvido no decurso da dissertação é essencialmente centrado no desenvolvimento de percepção robótica no contexto de condução autónoma.Computer vision and sensor fusion are subjects that are quite recent, however widely adopted in the development of autonomous robots that require
adaptability to their surrounding environment. This thesis gives an approach on both in order to achieve perception in the scope of autonomous driving.
The use of cameras to achieve this goal is a rather complex subject.
Unlike the classic sensorial devices that provide the same type of information with precision and achieve this in a deterministic way, the successive
images acquired by a camera are replete with the most varied information, that this ambiguous and extremely dificult to extract. The use of cameras
for robotic sensing is the closest we got within the similarities with what is of most importance in the process of human perception, the vision system. Computer vision is a scientific discipline that encompasses areas such as signal processing, artificial intelligence, mathematics, control theory,
neurobiology and physics.
The support platform in which the study within this thesis was developed, includes ROTA (RObô Triciclo Autónomo) and all elements comprising its
environment. In its context, are described approaches that introduced in the platform in order to develop solutions for all the challenges facing the robot in its environment: detection of lane markings and its consequent perception, obstacle detection, trafic lights, crosswalk and road maintenance area. It is also described a calibration system and implementation for the removal of the image perspective, developed in order to map the
elements perceived in actual real world distances. As a result of the perception system development, it is also addressed self-localization integrated in
a distributed architecture that allows navigation with long term planning.
All the work developed in the course of this work is essentially focused on robotic perception in the context of autonomous driving
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