996 resultados para Processamento de imagens - Técnicas digitais
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Given a large image set, in which very few images have labels, how to guess labels for the remaining majority? How to spot images that need brand new labels different from the predefined ones? How to summarize these data to route the user’s attention to what really matters? Here we answer all these questions. Specifically, we propose QuMinS, a fast, scalable solution to two problems: (i) Low-labor labeling (LLL) – given an image set, very few images have labels, find the most appropriate labels for the rest; and (ii) Mining and attention routing – in the same setting, find clusters, the top-'N IND.O' outlier images, and the 'N IND.R' images that best represent the data. Experiments on satellite images spanning up to 2.25 GB show that, contrasting to the state-of-the-art labeling techniques, QuMinS scales linearly on the data size, being up to 40 times faster than top competitors (GCap), still achieving better or equal accuracy, it spots images that potentially require unpredicted labels, and it works even with tiny initial label sets, i.e., nearly five examples. We also report a case study of our method’s practical usage to show that QuMinS is a viable tool for automatic coffee crop detection from remote sensing images.
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In this paper,we present a novel texture analysis method based on deterministic partially self-avoiding walks and fractal dimension theory. After finding the attractors of the image (set of pixels) using deterministic partially self-avoiding walks, they are dilated in direction to the whole image by adding pixels according to their relevance. The relevance of each pixel is calculated as the shortest path between the pixel and the pixels that belongs to the attractors. The proposed texture analysis method is demonstrated to outperform popular and state-of-the-art methods (e.g. Fourier descriptors, occurrence matrix, Gabor filter and local binary patterns) as well as deterministic tourist walk method and recent fractal methods using well-known texture image datasets.
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Dynamic texture is a recent field of investigation that has received growing attention from computer vision community in the last years. These patterns are moving texture in which the concept of selfsimilarity for static textures is extended to the spatiotemporal domain. In this paper, we propose a novel approach for dynamic texture representation, that can be used for both texture analysis and segmentation. In this method, deterministic partially self-avoiding walks are performed in three orthogonal planes of the video in order to combine appearance and motion features. We validate our method on three applications of dynamic texture that present interesting challenges: recognition, clustering and segmentation. Experimental results on these applications indicate that the proposed method improves the dynamic texture representation compared to the state of the art.
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Lung cancer is one of the most common types of cancer and has the highest mortality rate. Patient survival is highly correlated with early detection. Computed Tomography technology services the early detection of lung cancer tremendously by offering aminimally invasive medical diagnostic tool. However, the large amount of data per examination makes the interpretation difficult. This leads to omission of nodules by human radiologist. This thesis presents a development of a computer-aided diagnosis system (CADe) tool for the detection of lung nodules in Computed Tomography study. The system, called LCD-OpenPACS (Lung Cancer Detection - OpenPACS) should be integrated into the OpenPACS system and have all the requirements for use in the workflow of health facilities belonging to the SUS (Brazilian health system). The LCD-OpenPACS made use of image processing techniques (Region Growing and Watershed), feature extraction (Histogram of Gradient Oriented), dimensionality reduction (Principal Component Analysis) and classifier (Support Vector Machine). System was tested on 220 cases, totaling 296 pulmonary nodules, with sensitivity of 94.4% and 7.04 false positives per case. The total time for processing was approximately 10 minutes per case. The system has detected pulmonary nodules (solitary, juxtavascular, ground-glass opacity and juxtapleural) between 3 mm and 30 mm.
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The localization of mobile robots in indoor environments finds lots of problems such as accumulated errors and the constant changes that occur at these places. A technique called global vision intends to localize robots using images acquired by cameras placed in such a way that covers the place where the robots movement takes place. Localization is obtained by marks put on top of the robot. Algorithms applied to the images search for the mark on top of the robot and by finding the mark they are able to get the position and orientation of the robot. Such techniques used to face some difficulties related with the hardware capacity, fact that limited their execution in real time. However, the technological advances of the last years changed that situation and enabling the development and execution of such algorithms in plain capacity. The proposal specified here intends to develop a mobile robot localization system at indoor environments using a technique called global vision to track the robot and acquire the images, all in real time, intending to improve the robot localization process inside the environment. Being a localization method that takes just actual information in its calculations, the robot localization using images fit into the needs of this kind of place. Besides, it enables more accurate results and in real time, what is exactly the museum application needs.
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In several areas of health professionals (pediatricians, nutritionists, orthopedists, endocrinologists, dentists, etc.) are used in the assessment of bone age to diagnose growth disorders in children. Through interviews with specialists in diagnostic imaging and research done in the literature, we identified the TW method - Tanner and Whitehouse as the most efficient. Even achieving better results than other methods, it is still not the most used, due to the complexity of their use. This work presents the possibility of automation of this method and therefore that its use more widespread. Also in this work, they are met two important steps in the evaluation of bone age, identification and classification of regions of interest. Even in the radiography in which the positioning of the hands were not suitable for TW method, the identification algorithm of the fingers showed good results. As the use AAM - Active Appearance Models showed good results in the identification of regions of interest even in radiographs with high contrast and brightness variation. It has been shown through appearance, good results in the classification of the epiphysis in their stages of development, being chosen the average epiphysis finger III (middle) to show the performance. The final results show an average percentage of 90% hit and misclassified, it was found that the error went away just one stage of the correct stage.
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Objetivo: Trabalho realizado em ratos com o objetivo de estudar o efeito do Fator de Crescimento de Fibroblastos básico (FCFb) na cicatrização da aponeurose abdominal. Métodos: Foram usados 20 ratos Wistar separados aleatoriamente em 2 grupos iguais. Os animais foram anestesiados com pentobarbital sódico na dose de 20 mg/Kg por via intraperitoneal e submetidos a laparotomia mediana de 4 cm, cuja camada aponeurótica foi suturada com mononylon 5-0. No grupo I foi aplicada a dose de 5mg de FCFb sobre a sutura da aponeurose. No grupo II (controle) foi aplicada solução salina 0,9% sobre a linha se sutura. Após observação por 7 dias os animais foram mortos com superdose de anestésico. A camada aponeurótica com 1,5 cm de largura foi submetida a teste de resistência à tensão empregando a Máquina de Ensaios EMIC MF500. Biópsias das zonas de sutura foram processadas e coradas com HE e o tricômico de Masson. Os achados histopatológicos foram quantificados através de sistema digital (Image pro-plus) de captura e processamento de imagens. Os dados obtidos foram analisados pelo teste T com significância 0,05. Resultados: Nos animais do grupo I (experimental) a zona de sutura da camada aponeurótica suportou a carga de 1.103±103,39gf. A quantificação dos dados histopatológicos desse grupo atingiu a densidade média 226±29,32. No grupo II (controle) a carga suportada pela zona de sutura foi de 791,1±92,77 gf. Quando foram comparadas as médias das resistências à tensão dos dois grupos, observou-se uma diferença significante (p<0,01). O exame histopatológico das lâminas desse grupo relevou densidade média 114,1±17,01, correspondendo a uma diferença significante quando comparadas as médias dos dois grupos (p<0,01). Conclusão: Os dados permitem concluir que o FCFb contribuiu para aumentar a resistência da aponeurose suturada e para melhorar os parâmetros histopatológicos da cicatrização.
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Objetivo: Trabalho realizado em ratos com o objetivo de estudar o efeito do Fator de Crescimento de Fibroblastos básico (FCFb) na cicatrização da aponeurose abdominal. Métodos: Foram usados 20 ratos Wistar separados aleatoriamente em 2 grupos iguais. Os animais foram anestesiados com pentobarbital sódico na dose de 20 mg/Kg por via intraperitoneal e submetidos a laparotomia mediana de 4 cm, cuja camada aponeurótica foi suturada com mononylon 5-0. No grupo I foi aplicada a dose de 5mg de FCFb sobre a sutura da aponeurose. No grupo II (controle) foi aplicada solução salina 0,9% sobre a linha se sutura. Após observação por 7 dias os animais foram mortos com superdose de anestésico. A camada aponeurótica com 1,5 cm de largura foi submetida a teste de resistência à tensão empregando a Máquina de Ensaios EMIC MF500. Biópsias das zonas de sutura foram processadas e coradas com HE e o tricômico de Masson. Os achados histopatológicos foram quantificados através de sistema digital (Image pro-plus) de captura e processamento de imagens. Os dados obtidos foram analisados pelo teste T com significância 0,05. Resultados: Nos animais do grupo I (experimental) a zona de sutura da camada aponeurótica suportou a carga de 1.103±103,39gf. A quantificação dos dados histopatológicos desse grupo atingiu a densidade média 226±29,32. No grupo II (controle) a carga suportada pela zona de sutura foi de 791,1±92,77 gf. Quando foram comparadas as médias das resistências à tensão dos dois grupos, observou-se uma diferença significante (p<0,01). O exame histopatológico das lâminas desse grupo relevou densidade média 114,1±17,01, correspondendo a uma diferença significante quando comparadas as médias dos dois grupos (p<0,01). Conclusão: Os dados permitem concluir que o FCFb contribuiu para aumentar a resistência da aponeurose suturada e para melhorar os parâmetros histopatológicos da cicatrização.
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Gas-liquid two-phase flow is very common in industrial applications, especially in the oil and gas, chemical, and nuclear industries. As operating conditions change such as the flow rates of the phases, the pipe diameter and physical properties of the fluids, different configurations called flow patterns take place. In the case of oil production, the most frequent pattern found is slug flow, in which continuous liquid plugs (liquid slugs) and gas-dominated regions (elongated bubbles) alternate. Offshore scenarios where the pipe lies onto the seabed with slight changes of direction are extremely common. With those scenarios and issues in mind, this work presents an experimental study of two-phase gas-liquid slug flows in a duct with a slight change of direction, represented by a horizontal section followed by a downward sloping pipe stretch. The experiments were carried out at NUEM (Núcleo de Escoamentos Multifásicos UTFPR). The flow initiated and developed under controlled conditions and their characteristic parameters were measured with resistive sensors installed at four pipe sections. Two high-speed cameras were also used. With the measured results, it was evaluated the influence of a slight direction change on the slug flow structures and on the transition between slug flow and stratified flow in the downward section.
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A ocupação das margens do Ribeirão dos Pinheirinhos gerou fragmentação da mata ciliar, afetando a dinâmica ambiental do município de Brotas, São Paulo. Neste sentido, os diagnósticos ambientais podem atuar como subsídio indispensável para ações de minimização dos impactos ao meio a médio e longo prazo. O objetivo do trabalho foi diagnosticar as áreas de preservação permanente associadas aos recursos hídricos da bacia do Ribeirão dos Pinheirinhos, visando à determinação de áreas prioritárias à restauração florestal e manutenção hidrológica. Foi utilizado um banco de dados cartográfico digital e o SIG IDRISI Andes para análise espacial e processamento de imagens de satélite LandSat. Foram gerados mapas de: (i) uso e cobertura do solo, pela aplicação do algoritmo de classificação supervisionada de máxima verossimilhança; (ii) uso e cobertura do solo nas áreas de preservação permanente associadas a os recursos hídricos; (iii) distância às nascentes; e (iv) áreas prioritárias à restauração florestal. Houve predomínio dos cultivos agrícolas e solo exposto (73,70%), restando apenas 23,14% de remanescentes florestais. Foi observado que 32,09% das áreas de preservação permanente estão ocupadas inadequadamente, indicando a necessidade de investimento para conservação dos remanescentes florestais, melhor planejamento quanto ao uso do solo e adequação à legislação por parte dos órgãos públicos responsáveis, uma vez que 68,45% da área total foi classificada com prioridade alta a muito alta à restauração, percentual que tende a aumentar com o avanço das fronteiras agrícolas.
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Understanding spatial patterns of land use and land cover is essential for studies addressing biodiversity, climate change and environmental modeling as well as for the design and monitoring of land use policies. The aim of this study was to create a detailed map of land use land cover of the deforested areas of the Brazilian Legal Amazon up to 2008. Deforestation data from and uses were mapped with Landsat-5/TM images analysed with techniques, such as linear spectral mixture model, threshold slicing and visual interpretation, aided by temporal information extracted from NDVI MODIS time series. The result is a high spatial resolution of land use and land cover map of the entire Brazilian Legal Amazon for the year 2008 and corresponding calculation of area occupied by different land use classes. The results showed that the four classes of Pasture covered 62% of the deforested areas of the Brazilian Legal Amazon, followed by Secondary Vegetation with 21%. The area occupied by Annual Agriculture covered less than 5% of deforested areas; the remaining areas were distributed among six other land use classes. The maps generated from this project ? called TerraClass - are available at INPE?s web site (http://www.inpe.br/cra/projetos_pesquisas/terraclass2008.php)
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Na Bacia do Alto Paraguai o fogo é muito utilizado para manejo de pastagens, principalmente durante a estação seca. A determinação do risco de incêndio em áreas de vegetação é uma informação importante par auxiliar as práticas de manejo adequado ao uso do fogo. O objetivo deste trabalho foi realizar o mapeamento do risco de incêndio na Bacia do Alto Paraguai utilizando dados AVHRR-NOAA. A análise dos perfis temporais da Banda 1 e do NDVI nos meses de agosto, setembro e outubro de 2004 a 2008, em conjunto com os focos de calor detectados nas imagens NOAA, permitiu caracterizar o decréscimo da umidade da vegetação que proporciona a condição para ocorrência de incêndios. Os resultados mostraram que valores do fator de refletância da Banda 1 maiores que 5% e valores do NDVI menores que 0,40, podem estimar alto grau de risco de incêndio. O mapeamento do risco de incêndio utilizando dados AVHRR-NOAA demonstrou ter forte correlação com os focos de calor detectados nas imagens NOAA. O método mostrou ser viável e pode ser refinado para integrar os sistemas de prevenção de incêndio para alerta de queimadas e para tomadas de decisão para controle do fogo.
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Monitoring agricultural crops constitutes a vital task for the general understanding of land use spatio-temporal dynamics. This paper presents an approach for the enhancement of current crop monitoring capabilities on a regional scale, in order to allow for the analysis of environmental and socio-economic drivers and impacts of agricultural land use. This work discusses the advantages and current limitations of using 250m VI data from the Moderate Resolution Imaging Spectroradiometer (MODIS) for this purpose, with emphasis in the difficulty of correctly analyzing pixels whose temporal responses are disturbed due to certain sources of interference such as mixed or heterogeneous land cover. It is shown that the influence of noisy or disturbed pixels can be minimized, and a much more consistent and useful result can be attained, if individual agricultural fields are identified and each field's pixels are analyzed in a collective manner. As such, a method is proposed that makes use of image segmentation techniques based on MODIS temporal information in order to identify portions of the study area that agree with actual agricultural field borders. The pixels of each portion or segment are then analyzed individually in order to estimate the reliability of the temporal signal observed and the consequent relevance of any estimation of land use from that data. The proposed method was applied in the state of Mato Grosso, in mid-western Brazil, where extensive ground truth data was available. Experiments were carried out using several supervised classification algorithms as well as different subsets of land cover classes, in order to test the methodology in a comprehensive way. Results show that the proposed method is capable of consistently improving classification results not only in terms of overall accuracy but also qualitatively by allowing a better understanding of the land use patterns detected. It thus provides a practical and straightforward procedure for enhancing crop-mapping capabilities using temporal series of moderate resolution remote sensing data.
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Collecting ground truth data is an important step to be accomplished before performing a supervised classification. However, its quality depends on human, financial and time ressources. It is then important to apply a validation process to assess the reliability of the acquired data. In this study, agricultural infomation was collected in the Brazilian Amazonian State of Mato Grosso in order to map crop expansion based on MODIS EVI temporal profiles. The field work was carried out through interviews for the years 2005-2006 and 2006-2007. This work presents a methodology to validate the training data quality and determine the optimal sample to be used according to the classifier employed. The technique is based on the detection of outlier pixels for each class and is carried out by computing Mahalanobis distances for each pixel. The higher the distance, the further the pixel is from the class centre. Preliminary observations through variation coefficent validate the efficiency of the technique to detect outliers. Then, various subsamples are defined by applying different thresholds to exclude outlier pixels from the classification process. The classification results prove the robustness of the Maximum Likelihood and Spectral Angle Mapper classifiers. Indeed, those classifiers were insensitive to outlier exclusion. On the contrary, the decision tree classifier showed better results when deleting 7.5% of pixels in the training data. The technique managed to detect outliers for all classes. In this study, few outliers were present in the training data, so that the classification quality was not deeply affected by the outliers.
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