951 resultados para Imagens aéreas digitais
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Caracterizaram-se, por meio da ultrassonografia, as estruturas flexoras da porção distal dos membros de bovinos utilizando-se peças anatômicas da porção distal dos membros torácicos e pélvicos, provenientes de 20 novilhas mestiças da raça Nelore, com idades entre 24 e 36 meses. Para análise ultrassonográfica, foram estabelecidas cinco zonas de avaliação no plano transversal, denominadas, respectivamente, de zonas A, B, C, D e E, e duas em plano sagital, F-III e F-IV. Na face flexora, foram avaliados os tendões flexores digitais superficial e profundo, o músculo interósseo, o ligamento acessório do tendão flexor digital profundo e a manica flexoria, quanto à forma, limites, posição, ecogenicidade e mensurações das áreas transversais em cm². Sendo os resultados apresentados na forma descritiva e em tabelas, foi possível a caracterização das estruturas flexoras, identificando e determinando planos ultrassonográficos apropriados para a observação de imagens adequadas destes tecidos, além da obtenção de valores e parâmetros que possam ser utilizados como referência para esta espécie.
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The use of the maps obtained from remote sensing orbital images submitted to digital processing became fundamental to optimize conservation and monitoring actions of the coral reefs. However, the accuracy reached in the mapping of submerged areas is limited by variation of the water column that degrades the signal received by the orbital sensor and introduces errors in the final result of the classification. The limited capacity of the traditional methods based on conventional statistical techniques to solve the problems related to the inter-classes took the search of alternative strategies in the area of the Computational Intelligence. In this work an ensemble classifiers was built based on the combination of Support Vector Machines and Minimum Distance Classifier with the objective of classifying remotely sensed images of coral reefs ecosystem. The system is composed by three stages, through which the progressive refinement of the classification process happens. The patterns that received an ambiguous classification in a certain stage of the process were revalued in the subsequent stage. The prediction non ambiguous for all the data happened through the reduction or elimination of the false positive. The images were classified into five bottom-types: deep water; under-water corals; inter-tidal corals; algal and sandy bottom. The highest overall accuracy (89%) was obtained from SVM with polynomial kernel. The accuracy of the classified image was compared through the use of error matrix to the results obtained by the application of other classification methods based on a single classifier (neural network and the k-means algorithm). In the final, the comparison of results achieved demonstrated the potential of the ensemble classifiers as a tool of classification of images from submerged areas subject to the noise caused by atmospheric effects and the water column
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This work proposes the development of an intelligent system for analysis of digital mammograms, capable to detect and to classify masses and microcalcifications. The digital mammograms will be pre-processed through techniques of digital processing of images with the purpose of adapting the image to the detection system and automatic classification of the existent calcifications in the suckles. The model adopted for the detection and classification of the mammograms uses the neural network of Kohonen by the algorithm Self Organization Map - SOM. The algorithm of Vector quantization, Kmeans it is also used with the same purpose of the SOM. An analysis of the performance of the two algorithms in the automatic classification of digital mammograms is developed. The developed system will aid the radiologist in the diagnosis and accompaniment of the development of abnormalities
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abstract
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Image segmentation is one of the image processing problems that deserves special attention from the scientific community. This work studies unsupervised methods to clustering and pattern recognition applicable to medical image segmentation. Natural Computing based methods have shown very attractive in such tasks and are studied here as a way to verify it's applicability in medical image segmentation. This work treats to implement the following methods: GKA (Genetic K-means Algorithm), GFCMA (Genetic FCM Algorithm), PSOKA (PSO and K-means based Clustering Algorithm) and PSOFCM (PSO and FCM based Clustering Algorithm). Besides, as a way to evaluate the results given by the algorithms, clustering validity indexes are used as quantitative measure. Visual and qualitative evaluations are realized also, mainly using data given by the BrainWeb brain simulator as ground truth
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A distribuição radicular de duas cultivares de aspargo (New Jersey 220 e UC 157 F1), irrigadas por aspersão convencional, foi avaliada durante o ano de 1997 em solos de textura arenosa, em plantio experimental e comercial, respectivamente, nos Projetos de Irrigação de Bebedouro e Senador Nilo Coelho, em Petrolina (PE). O objetivo foi obter informações do sistema radicular do aspargo, empregando-se os métodos do monolito e do perfil de solo auxiliado pela análise de imagens digitais, para o manejo de solo e água nesse cultivo. Na área experimental, a maior parte da matéria seca, área e comprimento de raízes no perfil de solo e densidade de comprimento radicular foram encontradas até a profundidade de 0,4 m nas duas cultivares, enquanto que na comercial a maior parte da área e comprimento de raízes no perfil do solo estendeu-se até a profundidade de 0,6 m (cv. New Jersey 220). Nesses dois plantios, as raízes das cultivares atingiram a profundidade de 1 m. Na área experimental, a massa seca, a área e o comprimento no perfil de solo, e a densidade de comprimento radicular nas cultivares concentraram-se até a distância de 0,6 m à linha de plantas. No intervalo de diâmetro (d) de raízes 2
Sistema inteligente para detecção de manchas de óleo na superfície marinha através de imagens de SAR
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Oil spill on the sea, accidental or not, generates enormous negative consequences for the affected area. The damages are ambient and economic, mainly with the proximity of these spots of preservation areas and/or coastal zones. The development of automatic techniques for identification of oil spots on the sea surface, captured through Radar images, assist in a complete monitoring of the oceans and seas. However spots of different origins can be visualized in this type of imaging, which is a very difficult task. The system proposed in this work, based on techniques of digital image processing and artificial neural network, has the objective to identify the analyzed spot and to discern between oil and other generating phenomena of spot. Tests in functional blocks that compose the proposed system allow the implementation of different algorithms, as well as its detailed and prompt analysis. The algorithms of digital image processing (speckle filtering and gradient), as well as classifier algorithms (Multilayer Perceptron, Radial Basis Function, Support Vector Machine and Committe Machine) are presented and commented.The final performance of the system, with different kind of classifiers, is presented by ROC curve. The true positive rates are considered agreed with the literature about oil slick detection through SAR images presents
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There has been an increasing tendency on the use of selective image compression, since several applications make use of digital images and the loss of information in certain regions is not allowed in some cases. However, there are applications in which these images are captured and stored automatically making it impossible to the user to select the regions of interest to be compressed in a lossless manner. A possible solution for this matter would be the automatic selection of these regions, a very difficult problem to solve in general cases. Nevertheless, it is possible to use intelligent techniques to detect these regions in specific cases. This work proposes a selective color image compression method in which regions of interest, previously chosen, are compressed in a lossless manner. This method uses the wavelet transform to decorrelate the pixels of the image, competitive neural network to make a vectorial quantization, mathematical morphology, and Huffman adaptive coding. There are two options for automatic detection in addition to the manual one: a method of texture segmentation, in which the highest frequency texture is selected to be the region of interest, and a new face detection method where the region of the face will be lossless compressed. The results show that both can be successfully used with the compression method, giving the map of the region of interest as an input
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Digital Elevation Models (DEM) are numerical representations of a portion of the earth surface. Among several factors which affect the quality of a DEM, it should be emphasized the attention on the input data and the choice of the interpolating algorithm. On the other hand, several numerical models are used nowadays to characterize nearshore hydrodynamics and morphological changes in coastal areas, whose validation is based on field data collection. Independent on the complexity of the physical processes which are modeled, little attention has been given to the intrinsic bathymetric interpolation built within the numerical models of the specific application. Therefore, this study aims to investigate and to quantify the influence of the bathymetry, as obtained by a DEM, on the hydrodynamic circulation model at a coastal stretch, off the coast of the State of Rio Grande do Norte, Northeast Brazil. This coastal region is characterized by strong hydrodynamic and littoral processes, resulting in a very dynamic morphology with shallow coastal bathymetry. Important economic activities, such as oil exploitation and production, fisheries, salt ponds, shrimp farms and tourism, also bring impacts upon the local ecosystems and influence themselves the local hydrodynamics. This fact makes the region one of the most important for the development of the State, but also enhances the possibility of serious environmental accidents. As a hydrodynamic model, SisBaHiA® - Environmental Hydrodynamics System ( Sistema Básico de Hidrodinâmica Ambiental ) was chosen, for it has been successfully employed at several locations along the Brazilian coast. This model was developed at the Coastal and Oceanographical Engineering Group of the Ocean Engineering Program at the Federal University of Rio de Janeiro. Several interpolating methods were tested for the construction of the DEM, namely Natural Neighbor, Kriging, Triangulation with Linear Interpolation, Inverse Distance to a Power, Nearest Neighbor, and Minimum Curvature, all implemented within the software Surfer®. The bathymetry which was used as reference for the DEM was obtained from nautical charts provided by the Brazilian Hydrographic Service of the Brazilian Navy and from a field survey conducted in 2005. Changes in flow velocity and free surface elevation were evaluated under three aspects: a spatial vision along three profiles perpendicular to the coast and one profile longitudinal to the coast as shown; a temporal vision from three central nodes of the grid during 30 days; a hodograph analysis of components of speed in U and V, by different tidal cycles. Small, but negligible, variations in sea surface elevation were identified. However, the differences in flow and direction of velocities were significant, depending on the DEM
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Em Santa Bárbara D'Oeste,SP, foram realizados dois mapeamentos do uso da terra em área de 14.625 ha. No primeiro utilizou-se fotografias aéreas verticais pancromáticas (data de 25/6/78), na escala 1:35.000, e no segundo utilizou-se imagens orbitais do satélite LANDSAT-5 com sensor Thematic Mapper (data de 12/8/91), escala 1: 100.000, nas bandas 3, 4 e 5 e composição colorida 3/4/5. Para auxiliar a confecção desses mapas, obteve-se chaves de interpretação, tanto para as aerofotos como para as imagens orbitais. As fotografias aéreas proporcionaram um maior nível de detalhamento na identificação do uso da terra. A banda 3 e a composição colorida 3/4/5 foram as mais eficientes entre as imagens orbitais. Entre 1978 e 1991, a área de ocorrência de cana-de-açúcar permaneceu a mesma, as áreas de mata e pastagem diminuíram, enquanto que as áreas de reflorestamento e urbana aumentaram. Essa região teve sua capacidade de uso enquadrada, na maior parte, na classe IV: terras mais apropriadas para pastagens ou plantas perenes como a cana-de-açúcar, devendo-se aplicar técnicas intensivas de conservação, e com aptidão baseada em práticas agrícolas que refletem um alto nível tecnológico.
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Foram estudados, com o auxílio de fotografias aéreas, aspectos qualitativos e quantitativos do relevo e da rede de drenagem de solos de uma área de Santa Bárbara D'Oeste, SP. Esta região compreende 14.625 ha, onde foram selecionadas bacias hidrográficas de 3ª ordem de ramificação e amostras circulares de 5km². As unidades de mapeamento simples ou associações de solos são: Latossolo Vermelho Escuro, Podzólico, Litossolo + Podzólico, Terra Roxa Estruturada + Latossolo Roxo distrófico. Após a caracterização das feições fisiográficas, da área de ocorrência desses solos, foram realizados dois mapas morfopedológicos. No primeiro utilizou-se fotografias aéreas verticais pancromáticas na escala 1: 35.000 (data de 25/6/78) e no segundo imagens orbitais do sensor Thematic Mapper do LANDSAT-5, nas bandas 3, 4 e 5 e composição colorida 3/4/5 na escala 1: 100.000 (data de 12/9/91). As análises qualitativas e quantitativas do relevo (índice de declividade média) e rede de drenagem (densidade de drenagem, freqüência de rios, razão de textura) mostraram-se eficientes na diferenciação das unidades de solo estudadas, tanto em bacias hidrográficas como em amostras circulares. A utilização de fotografias aéreas, permitiu maior riqueza de detalhes na precisão dos limites das unidades de mapeamento e no maior número de unidades de mapeamento discriminadas em relação as imagens orbitais. A composição colorida 3/4/5 permitiu diferenciar os Latossolos argilosos dos Latossolos de textura média, assim como o Latossolo Húmico.
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Imagens CCD/CBERS-2, nas bandas espectrais CCD2, CCD3 e CCD4, dos anos de 2004 e 2005, de Mirante do Paranapanema - SP, foram transformadas em reflectância de superfície usando o modelo 5S de correção atmosférica e normalizadas radiometricamente. O objetivo principal foi caracterizar espectralmente áreas de pastagens de Brachiaria brizantha em fase de florescimento, isentas e infectadas com a doença mela-das-sementes da braquiária, possibilitando a sua detecção por meio da comparação entre os valores de reflectância de superfície denominada de Fator de Reflectância Bidirecional de Superfície (FRBS). Teve-se, também, o objetivo de avaliar a eficácia das imagens CCD/CBERS-2 para a obtenção de respostas espectrais de pastagens. Os dosséis sadios e doentes da Brachiaria brizantha foram identificados por meio da análise dos valores de reflectância e dos dados observados no Índice de Estresse Hídrico Acumulativo Relativo da Cultura (ACWSI) obtidos na área de estudo. Os resultados indicaram que as principais diferenças foram a diminuição da reflectância na banda CCD3 e o aumento da reflectância na banda CCD4 nas áreas doentes. A metodologia empregada com o uso de dados do sensor CCD/CBERS-2, associados ao ACWSI, mostrou-se eficaz para discriminar dosséis infectados com a mela-das-sementes da braquiária.
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The objective of this work is to identify, to chart and to explain the evolution of the soil occupation and the envirionment vulnerability of the areas of Canto do Amaro and Alto da Pedra, in the city of Mossoró-RN, having as base analyzes it multiweather of images of orbital remote sensors, the accomplishment of extensive integrated works of field to a Geographic Information System (GIS). With the use of inserted techniques of it analyzes space inserted in a (GIS), and related with the interpretation and analyzes of products that comes from the Remote Sensoriamento (RS.), make possible resulted significant to reach the objectives of this works. Having as support for the management of the information, the data set gotten of the most varied sources and stored in digital environment, it comes to constitute the geographic data base of this research. The previous knowledge of the spectral behavior of the natural or artificial targets, and the use of algorithms of Processing of Digital images (DIP), it facilitates the interpretation task sufficiently and searchs of new information on the spectral level. Use as background these data, was generated a varied thematic cartography was: Maps of Geology, Geomorfológicals Units soils, Vegetation and Use and Occupation of the soil. The crossing in environment SIG, of the above-mentioned maps, generated the maps of Natural and Vulnerability envirionmental of the petroliferous fields of I Canto do Amaro and Alto da Pedra-RN, working in an ambient centered in the management of waters and solid residuos, as well as the analysis of the spatial data, making possible then a more complex analysis of the studied area
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The aim of this study is to investigate the eco-environmental vulnerability, its changes, and its causes to develop a management system for application of eco-environmental vulnerability and risk assessment in the Apodi-Mossory estuary, Northeast Brazil. This analysis is focused on the interference of the landscape conditions, and its changes, due to the following factors: the oil and natural gas industry, tropical fruits industry, shrimp farms, marine salt industry, occupation of the sensitive areas; demand for land, vegetation degradation, siltation in rivers, severe flooding, sea level rise (SLR), coastal dynamics, low and flat topography, high ecological value and tourism in the region and the rapid growth of urbanization. Conventional and remote sensing data were analyzed using modeling techniques based on ArcGIS, ER-Mapper, ERDAS Imagine and ENVI software. Digital images were initially processed by Principal Component Analysis and transformation of the maximum fraction of noise, and then all bands were normalized to reduce errors caused by bands of different sizes. They were integrated in a Geographic Information System analysis to detect changes, to generate digital elevation models, geomorphic indices and other variables of the study area. A three band color combination of multispectral bands was used to monitor changes of land and vegetation cover from 1986 to 2009. This task also included the analysis of various secondary data, such as field data, socioeconomic data, environmental data and prospects growth. The main objective of this study was to improve our understanding of eco-environmental vulnerability and risk assessment; it´s causes basically show the intensity, its distribution and human-environment effect on the ecosystem, and identify the high and low sensitive areas and area of inundation due to future SLR, and the loss of land due to coastal erosion in the Apodi-Mossoró estuary in order to establish a strategy for sustainable land use. The developed model includes some basic factors such as geology, geomorphology, soils, land use / land cover, vegetation cover, slope, topography and hydrology. The numerical results indicate that 9.86% of total study area was under very high vulnerability, 29.12% high vulnerability, 52.90% moderate vulnerability and 2.23% were in the category of very low vulnerability. The analysis indicates that 216.1 km² and 362.8 km² area flooded on 1m and 10m in sea levels respectively. The sectors most affected were residential, industrial and recreational areas, agricultural land, and ecosystems of high environmental sensitivity. The results showed that changes in eco-environmental vulnerability have a significant impact on the sustainable development of the RN state, since the indicator is a function of sensitivity, exposure and status in relation to a level of damage. The model were presented as a tool to assist in indexing vulnerability in order to optimize actions and assess the implications of decisions makers and policies regarding the management of coastal and estuarine areas. In this context aspects such as population growth, degradation of vegetation, land use / land cover, amount and type of industrialization, SLR and government policies for environmental protection were considered the main factors that affect the eco-environmental changes over the last three decades in the Apodi-Mossoró estuary.
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This paper presents models of parameters of Sea Surface Layer (SSL), such as chlorophyll-a, sea surface temperature (SST), Primary Productivity (PP) and Total Suspended Matter (TSM) for the region adjacent to the continental shelf of Rio Grande do Norte (RN), Brazil. Concentrations of these parameters measured in situ were compared in time quasi-synchronous with images AQUA-MODIS between the years 2003 to 2011. Determination coefficients between samples in situ and bands reflectance sensor AQUA-MODIS were representative. From that, concentrations of SSL parameters were acquired for the continental shelf of the RN (eastern and northern) analyzing the geographic distribution of variation of these parameters between the years 2009-2012. Geographical and seasonal variations mainly influenced by global climate phenomena such as El Niño and La Niña, were found through the analysis of AQUA-MODIS images by Principal Components Analysis (PCA). Images show qualitatively the variance and availability of TSM in the regions, as well as their relationship with coastal erosion hotspots, monitored along the coast of the RN. In one of the areas identified as being of limited availability of TSM, we developed a methodology for assessment and evaluation of Digital Elevation Models (DEM) of beach surfaces (emerged and submerged sections) from the integration of topographic and bathymetric data measured in situ and accurately georeferenced compatible to studies of geomorphology and coastal dynamics of short duration. The methodology consisted of surveys with GNSS positioning operated in cinematic relative mode involved in topographic and bathymetric executed in relation to the stations of the geodetic network of the study area, which provided geodetic link to the Brazilian Geodetic System (GBS), univocal , fixed, and relatively stable over time. In this study Ponta Negra Beach, Natal / RN, was identified as a region with low variance and availability of MPS in the region off, as characterized by intense human occupation and intense coastal erosion in recent decades, which presents potential of the proposed methodology for accuracy and productivity, and the progress achieved in relation to the classical methods of surveying beach profiles