997 resultados para Extraction semi-automatique de termes


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Caatinga is an important laboratory for studies about arthropods adaptations and aclimatations because its precipitation is highly variable in time. We studied the effects of time variability over the composition of Arthropods in a caatinga area. The study was carried out at a preservation area on Almas Farm, São José dos Cordeiros, Paraíba. Samples were collected in two 100 m long parallel transects, separated for a 30 m distance, in a dense tree dominated caatinga area, between August 2007 and July 2008. Samples were collected in each transect every 10 m. Ten soil samples were taken from each transect, both at 0-5 cm (A) and 5-10 cm (B) depth, resulting in 40 samples each month. The Berlese funnel method was used for fauna extraction. We registered 26 orders and the arthropods density in the soil ranged from 3237 to 22774 individuals.m-2 from January 2007 to March 2008, respectively. There was no difference between layers A and B regarding orders abundance and richness. The groups recorded include groups with few records or that had no records in the Caatinga region yet as Pauropoda, Psocoptera, Thysanoptera, Protura and Araneae. Acari was the most abundant group, with 66,7% of the total number of individuals. Soil Arthropods presented a positive correlation with soil moisture, vegetal cover, precipitation and real evapotranspiration. Increases in fauna richness and abundance were registered in February, a month after the beginning of the rainy season. A periodic rain events in arid and semiarid ecosystems triggers physiological responses in edafic organisms, like arthropods. Edafic arthropods respond to time variability in the Caatinga biome. This fauna variation has to be considered in studies of this ecosystem, because the variation of Arthropods composition in soil can affect the dynamics of the food web through time

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This article proposes a method for 3D road extraction from a stereopair of aerial images. The dynamic programming (DP) algorithm is used to carry out the optimization process in the object-space, instead of usually doing it in the image-space such as the DP traditional methodologies. This means that road centerlines are directly traced in the object-space, implying that a mathematical relationship is necessary to connect road points in object and image-space. This allows the integration of radiometric information from images into the associate mathematical road model. As the approach depends on an initial approximation of each road, it is necessary a few seed points to coarsely describe the road. Usually, the proposed method allows good results to be obtained, but large anomalies along the road can disturb its performance. Therefore, the method can be used for practical application, although it is expected some kind of local manual edition of the extracted road centerline.

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Semi-automatic building detection and extraction is a topic of growing interest due to its potential application in such areas as cadastral information systems, cartographic revision, and GIS. One of the existing strategies for building extraction is to use a digital surface model (DSM) represented by a cloud of known points on a visible surface, and comprising features such as trees or buildings. Conventional surface modeling using stereo-matching techniques has its drawbacks, the most obvious being the effect of building height on perspective, shadows, and occlusions. The laser scanner, a recently developed technological tool, can collect accurate DSMs with high spatial frequency. This paper presents a methodology for semi-automatic modeling of buildings which combines a region-growing algorithm with line-detection methods applied over the DSM.

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This paper presents a dynamic programming approach for semi-automated road extraction from medium-and high-resolution images. This method is a modified version of a pre-existing dynamic programming method for road extraction from low-resolution images. The basic assumption of this pre-existing method is that roads manifest as lines in low-resolution images (pixel footprint> 2 m) and as such can be modeled and extracted as linear features. On the other hand, roads manifest as ribbon features in medium- and high-resolution images (pixel footprint ≤ 2 m) and, as a result, the focus of road extraction becomes the road centerlines. The original method can not accurately extract road centerlines from medium- and high- resolution images. In view of this, we propose a modification of the merit function of the original approach, which is carried out by a constraint function embedding road edge properties. Experimental results demonstrated the modified algorithm's potential in extracting road centerlines from medium- and high-resolution images.

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The purpose of this paper is to introduce a methodology for semi-automatic road extraction from aerial digital image pairs by using dynamic programming and epipolar geometry. The method uses both images from where each road feature pair is extracted. The operator identifies the corresponding road featuresand s/he selects sparse seed points along them. After all road pairs have been extracted, epipolar geometry is applied to determine the automatic point-to-point correspondence between each correspondent feature. Finally, each correspondent road pair is georeferenced by photogrammetric intersection. Experiments were made with rural aerial images. The results led to the conclusion that the methodology is robust and efficient, even in the presence of shadows of trees and buildings or other irregularities.

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A histological study was conducted of the alveolar bone healing process following tooth extraction of dehydrated rats after the implantation of fibrin adhesive (TISSUCOL™) associated to previous irrigation of the wound with a 5% epsilon aminocaproic acid solution (EACA). Seventy two rats were used, divided into three groups receiving different treatments after the surgical procedure. In group I, the gingival mucosa was sutured after extraction of the right upper incisor. In groups II and III, chronic dehydration was produced by water deprivation for 9 days (3 days in the preoperative period and 6 days in the postoperative period). In the animals of Group II, after tooth extraction, the gingival mucosa was sutured in the same way as performed in group I. In group III, after extraction, the dental socket was irrigated with 5% EACA, followed by implantation of the fibrin adhesive (TISSUCOL™). The mucosa was sutured in the same way as performed in the other groups. At 3, 7, 15 and 21 postoperative days, the animals were sacrificed in number of 6 for each group. Specimens containing the dental socket were removed and fixed in 10% formalin and decalcified in an equal part formic acid and sodium citrate solution. After routine processing, the specimens were embedded in paraffin for microtomy. We obtained 6 μm semi-serial slices that were stained with hematoxylin and eosin for histological evaluation. The results showed that the water deprivation in the pre- and postoperative periods caused a delay in the alveolar bone healing process. The use of the fibrin adhesive (TISSUCOL™) produced an improvement in the fibrinolytic picture caused by dehydration.

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In this paper is proposed a methodology for semiautomatic CBERS image orientation using roads as ground control. It is based on an iterative strategy involving three steps. In the first step, an operator identifies on the image the ground control roads and supplies along them a few seed points, which could be sparsely and coarsely distributed. These seed points are used by the dynamic programming algorithm for extracting the ground control roads from the image. In the second step, it is established the correspondences between points describing the ground control roads and the corresponding ones extracted from the image. In the last step, the corresponding points are used to orient the CBERS image by using the DLT (Direct Linear Transformation). The two last steps are iterated until the convergence of the orientation process is verified. Experimental results showed that the proposed methodology was efficient with several test images. In all cases the orientation process converged. Moreover, the estimated orientation parameters allowed the registration of check roads with pixel accuracy or better.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Pós-graduação em Ciências Cartográficas - FCT

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)