Segmentação de grãos de hematita em amostras de minério de ferro por análise de imagens de luz polarizada

• Ano de defesa: 2008
• Autor(a) principal: Rosa, Marlise
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; BR; Engenharia de Produção; UFSM; Programa de Pós-Graduação em Engenharia de Produção
• Palavras-chave em Português: Segmentação de imagens; Microscopia de luz polarizada; Reconhecimento de padrões; Análise multivariada; Minério de ferro; Hematita; Image segmentation; Polarized light microscopy; Pattern recognition; Multivariate analisys; Iron ore; Hematite; CNPQ::ENGENHARIAS::ENGENHARIA DE PRODUCAO
• Link de acesso: http://repositorio.ufsm.br/handle/1/8064

The aim of the present work is to classify co-registered pixels of stacks of polarized light images of iron ore into their respective crystalline grains or pores, thus producing grain segmented images that can be analyzed by their size, shape and orientation distributions, as well as their porosity and the size and morphology of the pores. Polished sections of samples of hematite-rich ore are digitally imaged in a rotating polarizer microscope at varying planepolarization angles. An image stack is produced for every field of view, where each image corresponds to a polarizer position. Any point in the sample is registered to the same pixel coordinates at all images in the stack. The resulting set of intensities for each pixel is directly related to the orientation of the crystal sampled at the corresponding position. Multivariate analysis of the sets of intensities leads to the classification of the pixels into their respective crystalline grains. Individual hematite grains of iron ore, as well as their pores, are segmented. The results are compared to those obtained by visual point counting methods.