Navegando por Assunto "Image processing"

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Acesso aberto (Open Access)
Uma abordagem híbrida e semiautomática para estimativa de regiões cobertas por nuvens e sombras em imagens de satélite: análise e avaliação
(Universidade Federal do Pará, 2014-03-31) SOUSA, Danilo Frazão; PELAES, Evaldo Gonçalves; http://lattes.cnpq.br/0255430734381362
The main goals of this work are to propose a more automatic and efficient algorithm to replace regions of clouds and shadows in satellite images as well as an index of reliability that is previously applied to each image, in order to measure the feasibility of the estimation of the regions covered by atmospheric components using that algorithm. The motivation comes from the problems caused by these atmospheric elements, among them: to impede the identification of objects of the image, to make the urban and environmental monitoring more difficult, and to interfere in crucial stages of digital image processing to extract information for the user, such as segmentation and classification. Through a hybrid approach is proposed a method for decomposing regions using a median non-linear low-pass filter, in order to map the regions of structure (homogeneous) and texture (heterogeneous) in the image. In these areas was applied restoration methods Inpainting by Smoothing based on Discrete Cosine Transform (DCT), and Exemplar-Based Texture Synthesis, respectively. It's important to note that the techniques have been modified to be able to work with images obtained through of satellite sensors with peculiar features such as large size and/or high spectral variation. Regarding to the reliability index, it aims to analyze the image that contains atmospheric interference and hence estimate how much reliable will be the redefinition, based on the percentage of cloud cover over the regions of texture and structure. This index is composed by combining the result of supervised and unsupervised algorithms involving three metrics: Average of Accuracy Global, Measure Of Structural Similarity (SSIM) and Average of Pixels Confidence. Finally, it was verified the effectiveness of these methods through a quantitative assessment (provided by the index) and qualitative (the images resulting from processing), showing the possible application of the techniques to solve the problems that motivated this work.
Acesso aberto (Open Access)
Estimativa de porosidade em lâminas petrográficas através da morfologia matemática binária
(Universidade Federal do Pará, 2013-08-02) CASTELO, Fernando Walleson Louzada; ANDRADE, André José Neves; http://lattes.cnpq.br/8388930487104926
Oil exploration in offshore basins needs for drilling boreholes with high angle and horizontal wells, aimed at optimizing the number of exploration targets hit by a single platform. In these cases, it is technically impossible to carry out the coring operations, which prevents core analysis for direct measurement of porosity. In some situations in formation evaluation the geological knowledge of the area may help when there is low confidence in the porosity values. For the semi-submerged basins, the lateral continuity of geologic layers may allow sampling of outcrops in the immersed part of the basin. In the case of offshore basins, may be collected hand samples in outcrops of analogous formations. A relatively common problem in a petrophysical laboratory is the extraction of plugs adapted to the measuring equipment, directly from rock samples collected from outcrops. On the other hand, for this type of rock sample is trivial to obtain thin sections. The objective of this work is to estimate porosity directly on the petrographic images using the image processing method, known as mathematical morphology, which aims to describe quantitatively the geometric structures (forms) in this image.
Acesso aberto (Open Access)
Método para extração de objetos de uma imagem de referência estática com estimativa das variações de iluminação
(Universidade Federal do Pará, 2009-12-04) OLIVEIRA, Jozias Parente de; PELAES, Evaldo Gonçalves; http://lattes.cnpq.br/0255430734381362; FREIRE, Raimundo Carlos Silvério; http://lattes.cnpq.br/4016576596215504
Video segmentation is a fundamental step in many vision systems including video surveillance and traffic monitoring. Background subtraction is a method typically used to segment moving regions in video sequences taken from a static camera by comparing each new frame to a model of the scene background. In this paper, a hardware system for video segmentation is proposed from algorithm to hardware architecture level. The video segmentation algorithm is aimed at fixed-point operations and improves a Gaussian background model by applying a two-stage linear compensation procedure to remove the undesirable subtraction results from noise and illumination changes. First, the algorithm was validated in MATLAB. Then, it was prototyped on an Altera field-programmable gate array platform (DE-2). At a clock rate of 100 MHz, the architecture can process 30 frames per second, where the image resolution is 640 x 507 pixels. The capability of the system is demonstrated for several video sequences.