72 resultados para Graph-based method
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One of the main problems in Computer Vision and Close Range Digital Photogrammetry is 3D reconstruction. 3D reconstruction with structured light is one of the existing techniques and which still has several problems, one of them the identification or classification of the projected targets. Approaching this problem is the goal of this paper. An area based method called template matching was used for target classification. This method performs detection of area similarity by correlation, which measures the similarity between the reference and search windows, using a suitable correlation function. In this paper the modified cross covariance function was used, which presented the best results. A strategy was developed for adaptative resampling of the patterns, which solved the problem of deformation of the targets due to object surface inclination. Experiments with simulated and real data were performed in order to assess the efficiency of the proposed methodology for target detection. The results showed that the proposed classification strategy works properly, identifying 98% of targets in plane surfaces and 93% in oblique surfaces.
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This paper presents a novel, fast and accurate appearance-based method for infrared face recognition. By introducing the Optimum-Path Forest classifier, our objective is to get good recognition rates and effectively reduce the computational effort. The feature extraction procedure is carried out by PCA, and the results are compared to two other well known supervised learning classifiers; Artificial Neural Networks and Support Vector Machines. The achieved performance asserts the promise of the proposed framework. ©2009 IEEE.
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In this paper a new partial differential equation based method is presented with a view to denoising images having textures. The proposed model combines a nonlinear anisotropic diffusion filter with recent harmonic analysis techniques. A wave atom shrinkage allied to detection by gradient technique is used to guide the diffusion process so as to smooth and maintain essential image characteristics. Two forcing terms are used to maintain and improve edges, boundaries and oscillatory features of an image having irregular details and texture. Experimental results show the performance of our model for texture preserving denoising when compared to recent methods in literature. © 2009 IEEE.
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This paper aims at extracting street centerlines from previously isolated street regions by using the image of laser scanning intensity. In this image, streets are easily identified, since they manifest as dark, elongate ribbons contrasting with background objects. The intensity image is segmented by using the region growing technique, which generates regions representing the streets. From these regions, the street centerlines are extracted in two manners. The first one is through the Steger lines detection method combined with a line length thresholding by which lines being shorter than a minimum length are removed. The other manner is by combining the skeletonization method of regions based on the Medial Axis Transform and with a pruning process to eliminate as much as possible the ramifications. Experiments showed that the Steger-based method provided results better than the method based on skeletonization.
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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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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Concept drift, which refers to non stationary learning problems over time, has increasing importance in machine learning and data mining. Many concept drift applications require fast response, which means an algorithm must always be (re)trained with the latest available data. But the process of data labeling is usually expensive and/or time consuming when compared to acquisition of unlabeled data, thus usually only a small fraction of the incoming data may be effectively labeled. Semi-supervised learning methods may help in this scenario, as they use both labeled and unlabeled data in the training process. However, most of them are based on assumptions that the data is static. Therefore, semi-supervised learning with concept drifts is still an open challenging task in machine learning. Recently, a particle competition and cooperation approach has been developed to realize graph-based semi-supervised learning from static data. We have extend that approach to handle data streams and concept drift. The result is a passive algorithm which uses a single classifier approach, naturally adapted to concept changes without any explicit drift detection mechanism. It has built-in mechanisms that provide a natural way of learning from new data, gradually "forgetting" older knowledge as older data items are no longer useful for the classification of newer data items. The proposed algorithm is applied to the KDD Cup 1999 Data of network intrusion, showing its effectiveness.
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The use of physical characteristics for human identification is known as biometrics. Among the many biometrics traits available, the fingerprint is the most widely used. The fingerprint identification is based on the impression patterns, as the pattern of ridges and minutiae, characteristics of first and second levels respectively. The current identification systems use these two levels of fingerprint features due to the low cost of the sensors. However, the recent advances in sensor technology, became possible to use third level features present within the ridges, such as the perspiration pores. Recent studies show that the use of third-level features can increase security and fraud protection in biometric systems, since they are difficult to reproduce. In addition, recent researches have also focused on multibiometrics recognition due to its many advantages. The goal of this research project was to apply fusion techniques for fingerprint recognition in order to combine minutia, ridges and pore-based methods and, thus, provide more robust biometrics recognition systems, and also to develop an automated fingerprint identification system using these three methods of recognition. We evaluated isotropic-based and adaptive-based automatic pore extraction methods, and the fusion of pore-based method with the identification methods based on minutiae and ridges. The experiments were performed on the public database PolyUHRF and showed a reduction of approximately 16% in the EER compared to the best results obtained by the methods individually
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
A new method for real time computation of power quality indices based on instantaneous space phasors
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One of the important issues about using renewable energy is the integration of dispersed generation in the distribution networks. Previous experience has shown that the integration of dispersed generation can improve voltage profile in the network, decrease loss, etc. but can create safety and technical problems as well. This work report the application of the instantaneous space phasors and the instantaneous complex power in observing performances of the distribution networks with dispersed generators in steady state. New IEEE apparent power definition, the so-called Buchholz-Goodhue effective apparent power, as well as new proposed power quality (oscillation) index in the three-phase distribution systems with unbalanced loads and dispersed generators, are applied. Results obtained from several case studies using IEEE 34 nodes test network are presented and discussed. (C) 2006 Elsevier B.V. All rights reserved.
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The dispersion of pollutants in the environment is an issue of great interest as it directly affects air quality, mainly in large cities. Experimental and numerical tools have been used to predict the behavior of pollutant species dispersion in the atmosphere. A software has been developed based on the control-volume based on the finite element method in order to obtain two-dimensional simulations of Navier-Stokes equations and heat or mass transportation in regions with obstacles, varying position of the pollutant source. Numeric results of some applications were obtained and, whenever possible, compared with literature results showing satisfactory accordance. Copyright (C) 2010 John Wiley & Sons, Ltd.
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This work presents a numerical study of the tri-dimensional convection-diffusion equation by the control-volume-based on finite-element method using quadratic hexahedral elements. Considering that the equation governing this problem in its main variable may represent several properties, including temperature, turbulent kinetic energy, viscous dissipation rate of the turbulent kinetic energy, specific dissipation rate of the turbulent kinetic energy, or even the concentration of a contaminant in a given medium, among others, the wide applicability of this problem is thus evidenced. Three cases of temperature distributions will be studied specifically in this work, in addition to one case of pollutant dispersion upon analysis of the concentration of a contaminant in a fixed flow point. Some comparisons will be carried out against works found in the open literature, while others will be done according to each phenomenon characteristics.