82 resultados para multiresolution
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This work proposes the development of a Computer System for Analysis of Mammograms SCAM, that aids the doctor specialist in the identification and analysis of existent lesions in digital mammograms. The computer system for digital mammograms processing will make use of a group of techniques of Digital Image Processing (DIP), with the purpose of aiding the medical professional to extract the information contained in the mammogram. This system possesses an interface of easy use for the user, allowing, starting from the supplied mammogram, a group of processing operations, such as, the enrich of the images through filtering techniques, the segmentation of areas of the mammogram, the calculation the area of the lesions, thresholding the lesion, and other important tools for the medical professional's diagnosis. The Wavelet Transform will used and integrated into the computer system, with the objective of allowing a multiresolution analysis, thus supplying a method for identifying and analyzing microcalcifications
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Digital signal processing (DSP) aims to extract specific information from digital signals. Digital signals are, by definition, physical quantities represented by a sequence of discrete values and from these sequences it is possible to extract and analyze the desired information. The unevenly sampled data can not be properly analyzed using standard techniques of digital signal processing. This work aimed to adapt a technique of DSP, the multiresolution analysis, to analyze unevenly smapled data, to aid the studies in the CoRoT laboratory at UFRN. The process is based on re-indexing the wavelet transform to handle unevenly sampled data properly. The was efective presenting satisfactory results
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The ionospheric effect is one of the major errors in GPS data processing over long baselines. As a dispersive medium, it is possible to compute its influence on the GPS signal with the ionosphere-free linear combination of L1 and L2 observables, requiring dual-frequency receivers. In the case of single-frequency receivers, ionospheric effects are either neglected or reduced by using a model. In this paper, an alternative for single-frequency users is proposed. It involves multiresolution analysis (MRA) using a wavelet analysis of the double-difference observations to remove the short- and medium-scale ionosphere variations and disturbances, as well as some minor tropospheric effects. Experiments were carried out over three baseline lengths from 50 to 450 km, and the results provided by the proposed method were better than those from dual-frequency receivers. The horizontal root mean square was of about 0.28 m (1 sigma).
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This work an algorithm for fault location is proposed. It contains the following functions: fault detection, fault classification and fault location. Mathematical Morphology is used to process currents obtained in the monitored terminals. Unlike Fourier and Wavelet transforms that are usually applied to fault location, the Mathematical Morphology is a non-linear operation that uses only basic operation (sum, subtraction, maximum and minimum). Thus, Mathematical Morphology is computationally very efficient. For detection and classification functions, the Morphological Wavelet was used. On fault location module the Multiresolution Morphological Gradient was used to detect the traveling waves and their polarities. Hence, recorded the arrival in the two first traveling waves incident at the measured terminal and knowing the velocity of propagation, pinpoint the fault location can be estimated. The algorithm was applied in a 440 kV power transmission system, simulated on ATP. Several fault conditions where studied and the following parameters were evaluated: fault location, fault type, fault resistance, fault inception angle, noise level and sampling rate. The results show that the application of Mathematical Morphology in faults location is very promising
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Integer carrier phase ambiguity resolution is the key to rapid and high-precision global navigation satellite system (GNSS) positioning and navigation. As important as the integer ambiguity estimation, it is the validation of the solution, because, even when one uses an optimal, or close to optimal, integer ambiguity estimator, unacceptable integer solution can still be obtained. This can happen, for example, when the data are degraded by multipath effects, which affect the real-valued float ambiguity solution, conducting to an incorrect integer (fixed) ambiguity solution. Thus, it is important to use a statistic test that has a correct theoretical and probabilistic base, which has became possible by using the Ratio Test Integer Aperture (RTIA) estimator. The properties and underlying concept of this statistic test are shortly described. An experiment was performed using data with and without multipath. Reflector objects were placed surrounding the receiver antenna aiming to cause multipath. A method based on multiresolution analysis by wavelet transform is used to reduce the multipath of the GPS double difference (DDs) observations. So, the objective of this paper is to compare the ambiguity resolution and validation using data from these two situations: data with multipath and with multipath reduced by wavelets. Additionally, the accuracy of the estimated coordinates is also assessed by comparing with the ground truth coordinates, which were estimated using data without multipath effects. The success and fail probabilities of the RTIA were, in general, coherent and showed the efficiency and the reliability of this statistic test. After multipath mitigation, ambiguity resolution becomes more reliable and the coordinates more precise. © Springer-Verlag Berlin Heidelberg 2007.
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Breast cancer is the most common cancer among women. In CAD systems, several studies have investigated the use of wavelet transform as a multiresolution analysis tool for texture analysis and could be interpreted as inputs to a classifier. In classification, polynomial classifier has been used due to the advantages of providing only one model for optimal separation of classes and to consider this as the solution of the problem. In this paper, a system is proposed for texture analysis and classification of lesions in mammographic images. Multiresolution analysis features were extracted from the region of interest of a given image. These features were computed based on three different wavelet functions, Daubechies 8, Symlet 8 and bi-orthogonal 3.7. For classification, we used the polynomial classification algorithm to define the mammogram images as normal or abnormal. We also made a comparison with other artificial intelligence algorithms (Decision Tree, SVM, K-NN). A Receiver Operating Characteristics (ROC) curve is used to evaluate the performance of the proposed system. Our system is evaluated using 360 digitized mammograms from DDSM database and the result shows that the algorithm has an area under the ROC curve Az of 0.98 ± 0.03. The performance of the polynomial classifier has proved to be better in comparison to other classification algorithms. © 2013 Elsevier Ltd. All rights reserved.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Ciência da Computação - IBILCE
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Pós-graduação em Engenharia Elétrica - FEIS
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A análise de ocorrências no sistema de energia elétrica é de fundamento mportância para uma operação segura, e para manter a qualidade da energia elétrica lornecida aos consumidores. As concessionárias do setor de energia elétrica usam equipamentos, chamados registradores de perturbação (RP's), para monitora diagnosticar problemas nos sistemas elétrico e de proteção. As formas de onda normalmente analisadas nos centros de operação das concessionárias, são aquelas geradas por eventos que quase sempre causam a aocrtul je linhas devido a operação dos relés comandados pelos dispositivos de proteção .Contudo, uma grande quantidade de registros armazenados que podem conte informações importantes sobre o comportamento e desempenho do sistema elétricl jeixa de ser analisada. O objetivo desse trabalho é usar os dados disponíveis nos centros de ontrole, operação das concessionárias de energia elétrica obtidos pelos RP's, para classificar e quantificar de forma automática sinais que caracterizem problemas de qualidade da energia, quanto a variações de tensão de curta duração: afundamentos, elevações e interrupções. O método proposto usa a transformada wavelet para obter um vetor característico para as tensões das fases A, B e C, e uma rede neural probabilística para classificação. Os sinais classificados como apresentando variações de curta duração são quantilicados quanto a duração e amplitude, usando-se as propriedades da análise nultiresolução da decomposição do sinal. Esses parâmetros, então, irão formar uma Jase de dados onde procedimentos de análise estatística podem ser usados para gerar relatórios com as características da qualidade da energia. Os resultados obtidos com a metodologia proposta para um sistema real são também apresentados.
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Essa dissertação tem por objetivo analisar a influência de famílias wavelets e suas ordens no desempenho de um algoritmo de localização de faltas a partir das ondas viajantes de dois terminais de uma linha de transmissão aérea. Tornou-se objetivo secundário a modelagem de um sistema elétrico de potência (SEP) para obtenção de um universo de faltas que validassem o localizador. Para isso, parte de um SEP da Eletrobrás-Eletronorte em 500/230 kV foi modelado no Alternative Transient Program (ATP) utilizando-se parâmetros reais. A Transformada Wavelet, via análise multiresolução (AMR), é empregada valendo-se de sua característica de localização temporal, permitindo caracterizações precisas de instantes de transitórios eletromagnéticos ocasionados por faltas, as quais geram ondas que ao se propagarem em direção aos terminais da linha contêm os tempos de propagação destas do local do defeito a tais terminais e podem ser convenientemente extraídos por tal transformada. Pela metodologia adotada no algoritmo, a diferença entre esses tempos determina com boa exatidão o local de ocorrência da falta sobre a linha. Entretanto, um dos agentes variantes do erro nessa estimação é a escolha da Wavelet usada na AMR dos sinais, sendo, portanto, a avaliação dessa escolha sobre o erro, objetivo principal do trabalho, justificada pela ainda inexistente fundamentação científica que garanta a escolha de uma wavelet ótima a uma certa aplicação. Dentre um leque de Wavelets discretas, obtiveram-se resultados adequados para 16 delas, havendo erros máximos inferiores aos 250 metros estipulados para a precisão. Duas Wavelets, a Db15 e a Sym17, sobressaíram-se ao errarem, respectivamente, 3,5 e 1,1 vezes menos que as demais. A metodologia empregada consta da: exportação dos dados das faltas do ATP para o MATLAB®; aplicação da transformação modal de Clarke; decomposição dos modos alfa e síntese dos níveis 1 de detalhes via AMR; cálculo de suas máximas magnitudes e determinação dos índices temporais; e por fim, a teoria das ondas viajantes equaciona e estima o local do defeito sobre a LT, sendo tudo isso programado no MATLAB e os erros de localização analisados estatisticamente no Microsoft Excell®. Ao final elaborou-se ainda uma GUI (Guide User Interface) para a Interface Homem-Máquina (IHM) do localizador, servindo também para análises gráficas de qualquer das contingências aplicadas ao SEP. Os resultados alcançados demonstram uma otimização de performance em razão da escolha da wavelet mais adequada ao algoritmo e norteiam para uma aplicação prática do localizador.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The representation of real objects in virtual environments has applications in many areas, such as cartography, mixed reality and reverse engineering. The generation of these objects can be performed in two ways: manually, with CAD (Computer Aided Design) tools, or automatically, by means of surface reconstruction techniques. The simpler the 3D model, the easier it is to process and store it. Multiresolution reconstruction methods can generate polygonal meshes in different levels of detail and, to improve the response time of a computer program, distant objects can be represented with few details, while more detailed models are used in closer objects. This work presents a new approach to multiresolution surface reconstruction, particularly interesting to noisy and low definition data, for example, point clouds captured with Kinect sensor
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Pós-graduação em Engenharia Elétrica - FEIS