917 resultados para multi-resolution image analysis
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The multipath effect affects the differential and relative positioning, even that one involving short baselines. So it is necessary to detect this effect, check the caused error level, and mainly, its removal. This paper aims at analysing and comparing some useful components in the detection of this effect. These components are the Signal to Noise Ratio (SNR), the values of MP1 and MP2 obtained from the TEQC software that indicates the multipath level in the carriers L1 and L2, the multipath repeatability in consecutive days and the elevation angle and the azimuth of the satellites. For this purpose, an experiment is carried out, comparing such components in the presence and the absence of reflector objects that cause the multipath. Not only there is clear multipath repeatability in the residuals, but it also appears in the measures SNR, MP1 and MP2, reaching up 99% of correlation. For reduction, at least, of the high frequency multipath effect, the Multi-Resolution Analysis using wavelets is applied in the double differences (DD) measures. Some statistical tests were accomplished, which indicate results improvement, and mainly, larger reliability in the solution of the ambiguities, reaching up 49% of improvement concerning the Ratio test without applying the proposed method.
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A new method for high-resolution analyses of hair surface charge density under ambient conditions is presented in this paper. Electrostatic force microscopy (EFM) is used here to analyze changes in surface charge density in virgin hair, bleached hair, and hair treated with a cationic polymer. The atomic force microscopy technique is used concomitantly to analyze morphological changes in hair roughness and thickness. The EFM images depict exactly how the polymer is distributed on the surface of the hair fiber. The EFM's powerful analytical tools enabled us to evaluate the varying degrees of interaction between the hair fiber surface charge density and the cationic polymer. The surface charge density and the polymer's distribution in the hair fibers are presented in the light of EFM measurements. © 2006 Society of Cosmetic Scientists and the Socièété Française de Cosmétologie.
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This paper seeks to apply a routine for highways detection through the mathematical morphology tools in high resolution image. The Mathematical Morphology theory consists of describing structures geometric presents quantitatively in the image (targets or features). This explains the use of the Mathematical Morphology in this work. As high resolution images will be used, the largest difficulty in the highways detection process is the presence of trees and automobiles in the borders tracks. Like this, for the obtaining of good results through the use of morphologic tools was necessary to choose the structuring element appropriately to be used in the functions. Through the appropriate choice of the morphologic operators and structuring elements it was possible to detect the highways tracks. The linear feature detection using mathematical morphology techniques, can contribute in cartographic applications, as cartographic products updating.
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A target tracking algorithm able to identify the position and to pursuit moving targets in video digital sequences is proposed in this paper. The proposed approach aims to track moving targets inside the vision field of a digital camera. The position and trajectory of the target are identified by using a neural network presenting competitive learning technique. The winning neuron is trained to approximate to the target and, then, pursuit it. A digital camera provides a sequence of images and the algorithm process those frames in real time tracking the moving target. The algorithm is performed both with black and white and multi-colored images to simulate real world situations. Results show the effectiveness of the proposed algorithm, since the neurons tracked the moving targets even if there is no pre-processing image analysis. Single and multiple moving targets are followed in real time.
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This research proposes to apply techniques of Mathematics Morphology to extract highways in digital images of high resolution, targeting the upgrade of cartographic products. Remote Sensing data and Mathematical Morphological techniques were integrated in the process of extraction. Mathematical Morphology's objective is to improve and extract the relevant information of the visual image. In order to test the proposed approach some morphological operators related to preprocess, were applied to the original images. Routines were implemented in the MATLAB environment. Results indicated good performances by the implemented operators. The integration of the technologies aimed to implement the semiautomatic extraction of highways with the purpose to use them in processes of cartographic updating.
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Aim To assess the dimensional characteristics, flexibility and torsional behaviour of nickel-titanium retreatment instruments. Methodology Using image analysis software and high-resolution digital images, the instrument length, tip angle, diameter at 3mm from the tip and the distance between the blades (pitch length) of the following eight instruments were measured (n=12 for each measurement parameter): the ProTaper Universal retreatment (PTU-R) D1, D2 and D3 instruments; the R-Endo R1, R2 and R3 retreatment instruments; and the Mtwo retreatment (Mtwo-R) sizes 25 and 15 retreatment instruments. Maximum torque and the angular deflection at fracture as well as the bending moment at 45° were measured (n=12) according to the International Standards Organisation (ISO) specification number 3630-1. Data were analysed using the analysis of variance (α=0.05). Results The length of the active part of the instruments was found to vary according to the depth of the canal into which they were designed to reach. The pitch length also increased along the active length. The PTU-R D1 and the Mtwo-R instruments had active tips. Measurements of the bending moment at 45° revealed that the Mtwo-R 15 instrument was the most flexible, whereas the PTU-R D1 was the least flexible. The maximum torque tended to increase as the instrument diameter at 3mm from the tip increased, whereas the angular deflection at fracture varied in the opposite direction. Conclusions The geometrical characteristics of the retreatment instruments and their flexibility and torsion behaviour were consistent with their intended clinical application. © 2011 International Endodontic Journal.
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Meteorological satellite and radar data comparative analysis allows to correlate the precipitation structures observed in both images. Such analysis would make feasible the extension of the range of ground-based meteorological radars. In addition to the different spatial and temporal resolution of these images this comparative analysis presents difficulties due to the effects of rotation and distortion, besides the different formats, projections, and coordinate systems. This work employed an approach based on a Gaussian adaptive filter in order to compare such images. The statistical results obtained from the comparison of the images are matched to those produced by other methods.
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In this paper we would like to shed light the problem of efficiency and effectiveness of image classification in large datasets. As the amount of data to be processed and further classified has increased in the last years, there is a need for faster and more precise pattern recognition algorithms in order to perform online and offline training and classification procedures. We deal here with the problem of moist area classification in radar image in a fast manner. Experimental results using Optimum-Path Forest and its training set pruning algorithm also provided and discussed. © 2011 IEEE.
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Different from the first attempts to solve the image categorization problem (often based on global features), recently, several researchers have been tackling this research branch through a new vantage point - using features around locally invariant interest points and visual dictionaries. Although several advances have been done in the visual dictionaries literature in the past few years, a problem we still need to cope with is calculation of the number of representative words in the dictionary. Therefore, in this paper we introduce a new solution for automatically finding the number of visual words in an N-Way image categorization problem by means of supervised pattern classification based on optimum-path forest. © 2011 IEEE.
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This study examined the relationships between gross chemical composition and ultrasonographic characteristics of the ram testes. Ten testes from sexually mature Karakul rams were scanned ex situ with an 8-MHz linear-array transducer, in a transverse and longitudinal plane. All ultrasonograms were saved as digital images and subjected to computerized analyses. Crude protein content was determined by the Kjeldahl method, moisture was determined with an oven-drying method, and fat was measured by the Soxhlet extraction of dried samples. Mean pixel values (r = -0.64, P = 0.04), pixel heterogeneity (standard deviation of pixel values; r = -0.64, P = 0.04) and maximum pixel intensity (r = -0.76, P = 0.01) were all negatively correlated with parenchymal protein content. Pixel heterogeneity correlated directly with extractable lipids (r = 0.66, P = 0.02). The quantitative correlations between echotextural and biochemical parameters found in the present experiment confirm the utility of ultrasonographic imaging combined with computer-assisted image analysis for determining changes in testicular histophysiology. © 2013 Elsevier Ltd. All rights reserved.
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Plant phenology is one of the most reliable indicators of species responses to global climate change, motivating the development of new technologies for phenological monitoring. Digital cameras or near remote systems have been efficiently applied as multi-channel imaging sensors, where leaf color information is extracted from the RGB (Red, Green, and Blue) color channels, and the changes in green levels are used to infer leafing patterns of plant species. In this scenario, texture information is a great ally for image analysis that has been little used in phenology studies. We monitored leaf-changing patterns of Cerrado savanna vegetation by taking daily digital images. We extract RGB channels from the digital images and correlate them with phenological changes. Additionally, we benefit from the inclusion of textural metrics for quantifying spatial heterogeneity. Our first goals are: (1) to test if color change information is able to characterize the phenological pattern of a group of species; (2) to test if the temporal variation in image texture is useful to distinguish plant species; and (3) to test if individuals from the same species may be automatically identified using digital images. In this paper, we present a machine learning approach based on multiscale classifiers to detect phenological patterns in the digital images. Our results indicate that: (1) extreme hours (morning and afternoon) are the best for identifying plant species; (2) different plant species present a different behavior with respect to the color change information; and (3) texture variation along temporal images is promising information for capturing phenological patterns. Based on those results, we suggest that individuals from the same species and functional group might be identified using digital images, and introduce a new tool to help phenology experts in the identification of new individuals from the same species in the image and their location on the ground. © 2013 Elsevier B.V. All rights reserved.
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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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Pós-graduação em Ciências Cartográficas - FCT
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Pós-graduação em Ciências Cartográficas - FCT