991 resultados para visible image sensor
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Depuis le début du XXIe siècle, un type particulier d’images a envahi l’espace public constitué par Internet : il s’agit des images principales de profil, ces images que les utilisateurs de sites de réseaux sociaux choisissent pour les représenter auprès des autres individus connectés. Comme le plus souvent il s’agit d’une image du corps de celui ou celle qui s’affiche ainsi, il est intéressant de s’intéresser à cette pratique en la rattachant à des pratiques plus anciennes. Dans un premier temps, cette étude présente donc une perspective socio-historique en notant la ressemblance de la pratique de l’image principale de profil avec celle de l’autoportrait et du portrait commandé. Cela permet de remarquer plusieurs points de rupture ou d’inflexion dans l’usage de ce type d’images, mais aussi d’en dégager les usages sociaux typiques. Ensuite, l’observation d’un lieu particulier d’Internet permet de tirer les conclusions suivantes : si l’usage principal de ces images est facile à expliquer, elles servent à symboliser une présence dans des lieux non accessibles aux corps sensibles, ces images montrent toujours des éléments qui permettent de déduire une position sociale et elles sont fondamentalement identiques aux images produites avant Internet. Ensuite, l’étude de ces images montre qu’il y a un véritable continuum dans la manière de dévoiler son intimité qui permet d’affirmer que la frontière entre public et privé n’existe pas sur Internet. Finalement, ces images montrent une absence de canon quant à leur production et une multiplicité des façons de se mettre en scène qui laissent à penser qu’elles sont devenues des symboles à part entière dans la communication qui peut s’établir entre des étrangers sur Internet.
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Dissertação (mestrado)—Universidade de Brasília, Instituto de Geociências, Programa de Pós-Graduação Stricto Sensu em Geociências Aplicadas, 2016.
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A camera maps 3-dimensional (3D) world space to a 2-dimensional (2D) image space. In the process it loses the depth information, i.e., the distance from the camera focal point to the imaged objects. It is impossible to recover this information from a single image. However, by using two or more images from different viewing angles this information can be recovered, which in turn can be used to obtain the pose (position and orientation) of the camera. Using this pose, a 3D reconstruction of imaged objects in the world can be computed. Numerous algorithms have been proposed and implemented to solve the above problem; these algorithms are commonly called Structure from Motion (SfM). State-of-the-art SfM techniques have been shown to give promising results. However, unlike a Global Positioning System (GPS) or an Inertial Measurement Unit (IMU) which directly give the position and orientation respectively, the camera system estimates it after implementing SfM as mentioned above. This makes the pose obtained from a camera highly sensitive to the images captured and other effects, such as low lighting conditions, poor focus or improper viewing angles. In some applications, for example, an Unmanned Aerial Vehicle (UAV) inspecting a bridge or a robot mapping an environment using Simultaneous Localization and Mapping (SLAM), it is often difficult to capture images with ideal conditions. This report examines the use of SfM methods in such applications and the role of combining multiple sensors, viz., sensor fusion, to achieve more accurate and usable position and reconstruction information. This project investigates the role of sensor fusion in accurately estimating the pose of a camera for the application of 3D reconstruction of a scene. The first set of experiments is conducted in a motion capture room. These results are assumed as ground truth in order to evaluate the strengths and weaknesses of each sensor and to map their coordinate systems. Then a number of scenarios are targeted where SfM fails. The pose estimates obtained from SfM are replaced by those obtained from other sensors and the 3D reconstruction is completed. Quantitative and qualitative comparisons are made between the 3D reconstruction obtained by using only a camera versus that obtained by using the camera along with a LIDAR and/or an IMU. Additionally, the project also works towards the performance issue faced while handling large data sets of high-resolution images by implementing the system on the Superior high performance computing cluster at Michigan Technological University.
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Atmospheric scattering plays a crucial rule in degrading the performance of electro optical imaging systems operating in the visible and infra-red spectral bands, and hence limits the quality of the acquired images, either through reduction of contrast or increase of image blur. The exact nature of light scattering by atmospheric media is highly complex and depends on the types, orientations, sizes and distributions of particles constituting these media, as well as wavelengths, polarization states and directions of the propagating radiation. Here we follow the common approach for solving imaging and propagation problems by treating the propagating light through atmospheric media as composed of two main components: a direct (unscattered), and a scattered component. In this work we developed a detailed model of the effects of absorption and scattering by haze and fog atmospheric aerosols on the optical radiation propagating from the object plane to an imaging system, based on the classical theory of EM scattering. This detailed model is then used to compute the average point spread function (PSF) of an imaging system which properly accounts for the effects of the diffraction, scattering, and the appropriate optical power level of both the direct and the scattered radiation arriving at the pupil of the imaging system. Also, the calculated PSF, properly weighted for the energy contributions of the direct and scattered components is used, in combination with a radiometric model, to estimate the average number of the direct and scattered photons detected at the sensor plane, which are then used to calculate the image spectrum signal to- noise ratio (SNR) in the visible near infra-red (NIR) and mid infra-red (MIR) spectral wavelength bands. Reconstruction of images degraded by atmospheric scattering and measurement noise is then performed, up to the limit imposed by the noise effective cutoff spatial frequency of the image spectrum SNR. Key results of this research are as follows: A mathematical model based on Mie scattering theory for how scattering from aerosols affects the overall point spread function (PSF) of an imaging system was developed, coded in MATLAB, and demonstrated. This model along with radiometric theory was used to predict the limiting resolution of an imaging system as a function of the optics, scattering environment, and measurement noise. Finally, image reconstruction algorithms were developed and demonstrated which mitigate the effects of scattering-induced blurring to within the limits imposed by noise.
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A miniaturised gas analyser is described and evaluated based on the use of a substrate-integrated hollow waveguide (iHWG) coupled to a microsized near-infrared spectrophotometer comprising a linear variable filter and an array of InGaAs detectors. This gas sensing system was applied to analyse surrogate samples of natural fuel gas containing methane, ethane, propane and butane, quantified by using multivariate regression models based on partial least square (PLS) algorithms and Savitzky-Golay 1(st) derivative data preprocessing. The external validation of the obtained models reveals root mean square errors of prediction of 0.37, 0.36, 0.67 and 0.37% (v/v), for methane, ethane, propane and butane, respectively. The developed sensing system provides particularly rapid response times upon composition changes of the gaseous sample (approximately 2 s) due the minute volume of the iHWG-based measurement cell. The sensing system developed in this study is fully portable with a hand-held sized analyser footprint, and thus ideally suited for field analysis. Last but not least, the obtained results corroborate the potential of NIR-iHWG analysers for monitoring the quality of natural gas and petrochemical gaseous products.
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Remotely sensed imagery has been widely used for land use/cover classification thanks to the periodic data acquisition and the widespread use of digital image processing systems offering a wide range of classification algorithms. The aim of this work was to evaluate some of the most commonly used supervised and unsupervised classification algorithms under different landscape patterns found in Rondônia, including (1) areas of mid-size farms, (2) fish-bone settlements and (3) a gradient of forest and Cerrado (Brazilian savannah). Comparison with a reference map based on the kappa statistics resulted in good to superior indicators (best results - K-means: k=0.68; k=0.77; k=0.64 and MaxVer: k=0.71; k=0.89; k=0.70 respectively for three areas mentioned). Results show that choosing a specific algorithm requires to take into account both its capacity to discriminate among various spectral signatures under different landscape patterns as well as a cost/benefit analysis considering the different steps performed by the operator performing a land cover/use map. it is suggested that a more systematic assessment of several options of implementation of a specific project is needed prior to beginning a land use/cover mapping job.
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In the last few years the sugar-cane mechanical harvested area has increased, especially in regions with appropriated slop. The use of this technology brings some inconveniences, such as, the increase in the percentage of extraneous matter, which causes the reduction of technological quality of the raw material, and losses in the field. Extraneous matter (trash) is composed of tops and leaves in major percentage, plus soil and roots, and eventually some metal parts. In the green cane harvest system the percentage of extraneous matter has a tendency to increase due to the great amount of vegetal matter to be processed. The increase in the blower fan speed to reduce the amount of extraneous matter can lead to an unacceptable economic level of raw material losses. The main objective of this work was, using a cane loss monitor, to evaluate and quantify the amount of visible losses of sugar cane through the primary extractor at two different fan speeds. Afterwards these losses were related to the harvester cleaning efficiency. The piezoelectric transducer shows a reasonable sensibility. The results show that the cleaning efficiency in the primary extractor (85% mean), the cane losses (between 5.68% and 2.15%) and fan speed are interrelated. The total losses and specially splinters (between 3.19% and 0.91%), showed a significant difference among the treatments.
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Universidade Estadual de Campinas . Faculdade de Educação Física
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PURPOSE: Juvenile idiopathic arthritis (JIA) has unknown etiology, and the involvement of the temporomandibular joint (TMJ) is rare in the early phase of the disease. The present article describes the use of computed tomography (CT) and magnetic resonance (MRI) images for the diagnosis of affected TMJ in JIA. CASE DESCRIPTION: A 12-year-old, female, Caucasian patient, with systemic rheumathoid arthritis and involvement of multiple joints was referred to the Imaging Center for TMJ assessment. The patient reported TMJ pain and limited opening of the mouth. The helical CT examination of the TMJ region showed asymmetric mandibular condyles, erosion of the right condyle and osteophyte-like formation. The MRI examination showed erosion of the right mandibular condyle, osteophytes, displacement without reduction and disruption of the articular disc. CONCLUSION: The disorders of the TMJ as a consequence of JIA must be carefully assessed by modern imaging methods such as CT and MRI. CT is very useful for the evaluation of discrete bone changes, which are not identified by conventional radiographs in the early phase of JIA. MRI allows the evaluation of soft tissues, the identification of acute articular inflammation and the differentiation between pannus and synovial hypertrophy.
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OBJETIVO: Desenvolver simulação computadorizada de ablação para produzir lentes de contato personalizadas a fim de corrigir aberrações de alta ordem. MÉTODOS: Usando dados reais de um paciente com ceratocone, mensurados em um aberrômetro ("wavefront") com sensor Hartmann-Shack, foram determinados as espessuras de lentes de contato que compensam essas aberrações assim como os números de pulsos necessários para fazer ablação as lentes especificamente para este paciente. RESULTADOS: Os mapas de correção são apresentados e os números dos pulsos foram calculados, usando feixes com a largura de 0,5 mm e profundidade de ablação de 0,3 µm. CONCLUSÕES: Os resultados simulados foram promissores, mas ainda precisam ser aprimorados para que o sistema de ablação "real" possa alcançar a precisão desejada.
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In this communication we describe the application of a conductive polymer gas sensor as an air pressure sensor. The device consists of a thin doped poly(4'-hexyloxy-2,5-biphenylene ethylene) (PHBPE) film deposited on an interdigitated metallic electrode. The sensor is cheap, easy to fabricate, lasts for several months, and is suitable for measuring air pressures in the range between 100 and 700 mmHg.
Caracterização de feições oceanográficas na plataforma de Santa Catarina através de imagens orbitais
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Este trabalho tem por objetivo identificar e caracterizar as feições oceanográficas de pequena e mesoescala que ocorrem na plataforma continental de Santa Catarina (SC). Foram empregadas imagens de temperatura e concentração de clorofila da superfície do mar (TSM e CSM), obtidas pelo sensor MODIS. Foi selecionada uma imagem diária para cada mês do ano de 2003, excetuando dezembro, onde procurou-se avaliar efeitos sazonais. As feições oceanográficas foram observadas através da aplicação de diferentes níveis de contraste e paletas de cores para realce. Foram identificadas feições como vórtices, meandros, cogumelos, plumas, filamentos, frentes e áreas de ressurgências. Os resultados indicam que no verão a distribuição superficial em mesoescala da temperatura é mais homogênea, levando a um número menor de feições observáveis. O fenômeno de ressurgência costeira em escala localizada ao sul da Ilha de SC e junto à costa foi observado nos meses de novembro, janeiro e fevereiro. Durante o outono e o inverno as imagens apresentaram maior grau de complexidade, principalmente devido à presença da frente costeira do Prata, com características de menor temperatura e maiores valores de clorofila.
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Fifty Bursa of Fabricius (BF) were examined by conventional optical microscopy and digital images were acquired and processed using Matlab® 6.5 software. The Artificial Neuronal Network (ANN) was generated using Neuroshell® Classifier software and the optical and digital data were compared. The ANN was able to make a comparable classification of digital and optical scores. The use of ANN was able to classify correctly the majority of the follicles, reaching sensibility and specificity of 89% and 96%, respectively. When the follicles were scored and grouped in a binary fashion the sensibility increased to 90% and obtained the maximum value for the specificity of 92%. These results demonstrate that the use of digital image analysis and ANN is a useful tool for the pathological classification of the BF lymphoid depletion. In addition it provides objective results that allow measuring the dimension of the error in the diagnosis and classification therefore making comparison between databases feasible.