Construction and test of low cost X-ray tomography scanner for physical-chemical analysis and nondestructive inspections

X-ray computed tomography (CT) refers to the cross-sectional imaging of an object measuring the transmitted radiation at different directions. In this work, we describe the development of a low cost micro-CT X-ray scanner that is being developed for nondestructive testing. This tomograph operates using a microfocus X-ray source and contains a silicon photodiode as detectors. The performance of the system, by its spatial resolution, has been estimated through its Modulation Transfer Function - MTF and the obtained value at 10% of MTF is 661 μm. It was built as a general purpose nondestructive testing device. © 2009 American Institute of Physics.

Is it possible to make pixel-based radar image classification user-friendly?

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.

Image categorization through optimum path forest and visual words

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.

Preliminary assessment of the quantitative relationships between testicular tissue composition and ultrasonographic image attributes in the ram

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.

Evolução do processo de espermiação em machos de Piau, Leporinus macrocephalus, hormonalmente induzidos à reprodução

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise microestrutural de revestimentos usados no reparo de turbinas hidráulicas danificadas pela cavitação

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Emprego da fotografia digital para avaliação da topografia microscópia da pele

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Alterações testiculaes no diabetes aloxânico no rato: estudo morfométrico e ultraestrutural dos túbulos seminíferos

Pós-graduação em Bases Gerais da Cirurgia - FMB

Estudo morfológico e cinético da corrosão por pites em liga de alumínio 1050

Pós-graduação em Engenharia Mecânica - FEG

Desenvolvimento de um sistema de análise de imagem para quantificação do tamanho e distribuição de partículas de desgaste

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

O efeito da técnica de inclusão para fundição de titânio CP na fluidez, rusogidade, camada de reação e desajuste marginal

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise do processo de fresamento de MDF em centro de usinagem CNC

Pós-graduação em Engenharia Mecânica - FEG

Cinética de crescimento do fungo termófilo Myceliophthora thermophila M. 7.7 em cultivo no estado sólido

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Deriving vegetation indices for phenology analysis using genetic programming

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Image segmentation through combined methods: watershed transform, unsupervised distance learning and normalized cut

Research on image processing has shown that combining segmentation methods may lead to a solid approach to extract semantic information from different sort of images. Within this context, the Normalized Cut (NCut) is usually used as a final partitioning tool for graphs modeled in some chosen method. This work explores the Watershed Transform as a modeling tool, using different criteria of the hierarchical Watershed to convert an image into an adjacency graph. The Watershed is combined with an unsupervised distance learning step that redistributes the graph weights and redefines the Similarity matrix, before the final segmentation step using NCut. Adopting the Berkeley Segmentation Data Set and Benchmark as a background, our goal is to compare the results obtained for this method with previous work to validate its performance.