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We present a method for extracting contours from digital images, using techniques from computational geometry. Our approach is different from traditional pixel-based methods in image processing. Instead of working directly with pixels, we extract a set of oriented feature points from the input digital images, then apply classical geometric techniques, such as clustering, linking, and simplification, to find contours among these points. Experiments on synthetic and natural images show that our method can effectively extract contours, even from images with considerable noise; moreover, the extracted contours have a very compact representation.

The purpose of this study was the hardware implementation of a real time moving object contour extraction.Segmentation of image frames to isolate moving objects followed by contour extraction using digitalmorphology was carried out in this work. Segmentation using temporal difference with median thresholdingapproach was implemented, experimental methods were used to determine the suitable morphological operatorsalong with their structuring elements dimensions to provide the optimum contour extraction.The detector with image resolution of 1280 x1024 pixels and frame rate of 60 Hz was successfully implemented,the results indicate the effect of proper use of morphological operators for post processing and contourextraction on the overall efficiency of the system. An alternative segmentation method based on Stauffer & Grimson algorithm was investigated and proposed which promises better system performance at the expense ofimage resolution and frame rate

Contour extraction of Drosophila embryos is an important step to build a computational system for pattern matching of embryonic images which aids in the discovery of genes. Automatic contour extraction of embryos is challenging due to several image variations such as size, shape, orientation and neigh- boring embryos such as touching and non-touching embryos. In this thesis, we introduce a framework for contour extraction based on the connected components in the gaussian scale space of an embryonic image. The active contour model is applied on the images to refine embryo contours. Data cleaning methods are applied to smooth the jaggy contours caused by blurred embryo boundaries. The scale space theory is applied to improve the performance of the result. The active contour adjusts better to the object for finer scales. The proposed framework contains three components. In the first component, we find the connected components of the image. The second component is to find the largest component of the image. Finally, we analyze the largest component across scales by selecting the optimal scale corresponding to the largest component having largest area. The optimal scale at which maximum area is attained is assumed to give information about the feature being extracted. We tested the proposed framework on BDGP images, and the results achieved promising accuracy in extracting the targeting embryo.

This thesis tries to answer if a semi-automatic tool can speed up the process of segmenting tumors to find the area of a slice in the tumor or the volume of the entire tumor. A few different 2D semi-automatic tools were considered. The final choice was to implement live-wire. The implemented live-wire was evaluated and improved upon with hands-on testing from developers. Two methods were found for extending live-wire to 3D bodies. The first method was to interpolate the seed points and create new contours using the new seed points. The second method was to let the user segment contours in two orthogonal projections. The intersections between those contours and planes in the third orthogonal projection were then used to create automatic contours in this third projection. Both tools were implemented and evaluated. The evaluation compared the two tools to manual segmentation on two cases posing different difficulties. Time-on-task and accuracy were measured during the evaluation. The evaluation revealed that the semi-automatic tools could indeed save the user time while maintaining acceptable (80%) accuracy. The significance of all results were analyzed using two-tailed t-tests.

Orientador: Aluir Porfírio Dal Poz / Banca: Nilton Nobuhiro Imai / Banca: Maurício Galo / Banca: Edson Aparecido Mitishita / Resumo: As metodologias para a extração automática de telhados desempenham um papel importante no contexto de aquisição de informação espacial para Sistemas de Informação Geográficas (SIG). Neste sentido, este trabalho propõe uma metodologia para extração automática de contornos de telhado de edifícios utilizando dados de varredura a laser. A metodologia baseiase em duas etapas principais: 1) Extração de regiões altas (edifícios, árvores etc.) de um Modelo Digital de Elevação (MDE) gerado a partir dos dados laser; 2) Extração das regiões altas que correspondem a contornos de telhados. Na primeira etapa são utilizadas as técnicas de divisão recursiva, via estrutura quadtree e de fusão Bayesiana de regiões considerando Markov Random Field (MRF). Inicialmente a técnica de divisão recursiva é usada para particionar o MDE em regiões homogêneas. No entanto, devido a ligeiras diferenças de altura no MDE, nesta etapa a fragmentação das regiões pode ser relativamente alta. Para minimizar essa fragmentação, a técnica de fusão Bayesiana de regiões é aplicada nos dados segmentados. Utiliza-se para tanto um modelo hierárquico, cujas alturas médias das regiões dependem de uma média geral e de um efeito aleatório, que incorpora a relação de vizinhança entre elas. A distribuição a priori para o efeito aleatório é especificada como um modelo condicional auto-regressivo (CAR). As distribuições a posteriori para os parâmetros de interesse foram obtidas utilizando o Amostrador de Gibbs. Na segunda etapa os contornos de telhados são identificados entre todos os objetos altos extraídos na etapa anterior. Levando em conta algumas propriedades de telhados e as medidas de alguns atributos (por exemplo, área, retangularidade, ângulos entre eixos principais de objetos) é construída uma função de energia a partir do modelo MRF. / Abstract: Methodologies for automatic building roof extraction are important in the context of spatial information acquisition for geographical information systems (GIS). Thus, this work proposes a methodology for automatic extraction of building roof contour from laser scanning data. The methodology is based on two stages: 1) Extraction of high regions (buildings, trees etc.) from a Digital Elevation Model (DEM) derived from laser scanning data; 2) Building roof contour extraction. In the first stage is applied the recursive splitting technique using the quadtree structure followed by a Bayesian merging technique considering Markov Random Field (MRF) model. The recursive splitting technique subdivides the DEM into homogeneous regions. However, due to slight height differences in the DEM, in this stage the region fragmentation can be relatively high. In order to minimize the fragmentation, a region merging technique based on the Bayesian framework is applied to the previously segmented data. Thus, a hierarchical model is proposed, whose height values in the data depend on a general mean plus a random effect. The prior distribution for the random effects is specified by the Conditional Autoregressive (CAR) model. The posterior probability distributions are obtained by the Gibbs sampler. In the second stage the building roof contours are identified among all high objects extracted previously. / Doutor

Localization of Drosophila embryos in images is a fundamental step in an automatic computational system for the exploration of gene-gene interaction on Drosophila. Contour extraction of embryonic images is challenging due to many variations in embryonic images. In the thesis work, we develop a localization framework based on the analysis of connected components of edge pixels in a scale space. We propose criteria to select optimal scales for embryonic localization. Furthermore, we propose a scale mapping strategy to compress the range of a scale space in order to improve the efficiency of the localization framework. The effectiveness of the proposed framework and the scale mapping strategy are validated in our experiments.

Made available in DSpace on 2014-06-11T19:30:31Z (GMT). No. of bitstreams: 0 Previous issue date: 2007-03-29Bitstream added on 2014-06-13T18:40:49Z : No. of bitstreams: 1 galvanin_eas_dr_prud.pdf: 5173646 bytes, checksum: aae51c2e230277eff607da015efe8a65 (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / As metodologias para a extração automática de telhados desempenham um papel importante no contexto de aquisição de informação espacial para Sistemas de Informação Geográficas (SIG). Neste sentido, este trabalho propõe uma metodologia para extração automática de contornos de telhado de edifícios utilizando dados de varredura a laser. A metodologia baseiase em duas etapas principais: 1) Extração de regiões altas (edifícios, árvores etc.) de um Modelo Digital de Elevação (MDE) gerado a partir dos dados laser; 2) Extração das regiões altas que correspondem a contornos de telhados. Na primeira etapa são utilizadas as técnicas de divisão recursiva, via estrutura quadtree e de fusão Bayesiana de regiões considerando Markov Random Field (MRF). Inicialmente a técnica de divisão recursiva é usada para particionar o MDE em regiões homogêneas. No entanto, devido a ligeiras diferenças de altura no MDE, nesta etapa a fragmentação das regiões pode ser relativamente alta. Para minimizar essa fragmentação, a técnica de fusão Bayesiana de regiões é aplicada nos dados segmentados. Utiliza-se para tanto um modelo hierárquico, cujas alturas médias das regiões dependem de uma média geral e de um efeito aleatório, que incorpora a relação de vizinhança entre elas. A distribuição a priori para o efeito aleatório é especificada como um modelo condicional auto-regressivo (CAR). As distribuições a posteriori para os parâmetros de interesse foram obtidas utilizando o Amostrador de Gibbs. Na segunda etapa os contornos de telhados são identificados entre todos os objetos altos extraídos na etapa anterior. Levando em conta algumas propriedades de telhados e as medidas de alguns atributos (por exemplo, área, retangularidade, ângulos entre eixos principais de objetos) é construída uma função de energia a partir do modelo MRF. / Methodologies for automatic building roof extraction are important in the context of spatial information acquisition for geographical information systems (GIS). Thus, this work proposes a methodology for automatic extraction of building roof contour from laser scanning data. The methodology is based on two stages: 1) Extraction of high regions (buildings, trees etc.) from a Digital Elevation Model (DEM) derived from laser scanning data; 2) Building roof contour extraction. In the first stage is applied the recursive splitting technique using the quadtree structure followed by a Bayesian merging technique considering Markov Random Field (MRF) model. The recursive splitting technique subdivides the DEM into homogeneous regions. However, due to slight height differences in the DEM, in this stage the region fragmentation can be relatively high. In order to minimize the fragmentation, a region merging technique based on the Bayesian framework is applied to the previously segmented data. Thus, a hierarchical model is proposed, whose height values in the data depend on a general mean plus a random effect. The prior distribution for the random effects is specified by the Conditional Autoregressive (CAR) model. The posterior probability distributions are obtained by the Gibbs sampler. In the second stage the building roof contours are identified among all high objects extracted previously.

Made available in DSpace on 2016-03-15T19:38:07Z (GMT). No. of bitstreams: 1 Ivan Gonzalez.pdf: 604401 bytes, checksum: 1652d5996de760edf38fd1a3bb2e64e4 (MD5) Previous issue date: 2006-09-18 / A variant of Kuramoto's model for phase oscillators with dynamic coupling is studied. The coupling weight is adjusted by the phase difference resulting in a connection which is strengthened for synchronized oscillators and weakened for non-synchronized oscillators. Equilibrium solutions and their stabilities are presents and it is shown the occurrence of saddle-node and Hopf bifurcations. It is shown that networks formed by such oscillators can be used for detecting image border. / Uma variante do modelo de Kuramoto para osciladores de fase com acoplamento dinâmico é estudada. A intensidade do acoplamento é ajustada pela diferença de fases dos osciladores, de forma que a conexão é reforçada para osciladores sincronizados e enfraquecida para osciladores não sincronizados. As soluções de equilíbrio e suas estabilidades são apresentadas, e mostra-se que o sistema apresenta bifurcações sela-nó e de Hopf. Mostra-se que redes formadas com esses osciladores podem ser usadas para extrair o contorno de figuras.

This work involves the design and implementation of a real-time Machine Vision-based Human Computer Interface (HCI) that analyzes and interprets a music conductor's gestures to detect the musical "beat". This HCI system interfaces directly with the "Virtual Orchestra", an electronic MIDI sequenced "orchestra". Prior to the development of this HCI system, the real time control of the tempo of the "Virtual Orchestra" could only be controlled by tapping a tempo on a MIDI controller device--a process that is foreign to most music conductors. The real-time beat information detected by this HCI system allows a conductor to conduct the "Virtual Orchestra" as if it were a live orchestra. This system was developed using the Broadway real-time color image capture board manufactured by Data Translation, Incorporated. The implementation involved the use of Microsoft Visual C++, Microsoft Foundation Classes (MFC) for the Graphical User Interface (GUI), Video For Windows (VFW), MIDI note generation, and Intel assembly level code optimization. Algorithms were developed for rapid RGB color thresholding, multiple contour extraction, fast contour based area and center of mass calculations, and gesture interpretation. Real time, live-video interpretation has been achieved and an end-to-end system has been demonstrated in conjuction with a MIDI sequencer.