Road segment delineation using active testing principle and an edge-based post-processing strategy

This paper presents a semi-automated method for extracting road segments from medium-resolution images based on active testing and edge analysis. The method is based on two sequential and independent stages. Firstly, an active testing method is used to extract an approximated road centreline which is based on a sequential and local exploitation of the image. Secondly, an iterative strategy based on edge analysis and the approximated centreline is used to measure precisely the road centreline. Based on the results obtained using medium-resolution test images, the method seems to be very promising. In general, the method proved to be very accurate whenever the roads are characterized by two well-defined anti-parallel edges and robust even in the presence of larger obstacles such as trees and shadows.

Post-processing of sequential indicator simulation realizations for modeling geologic bodies

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

An image processing method for morphology characterization and pitting corrosion evaluation

A digital image processing and analysis method has been developed to classify shape and evaluate size and morphology parameters of corrosion pits. This method seems to be effective to analyze surfaces with low or high degree of pitting formation. Theoretical geometry data have been compared against experimental data obtained for titanium and aluminum alloys subjected to different corrosion tests. (C) 2002 Elsevier B.V. B.V. All rights reserved.

A new processing method of CaZn2(OH)(6)center dot 2H(2)O powders: Photoluminescence and growth mechanism

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Post-processing association rules with clustering and objective measures

The post-processing of association rules is a difficult task, since a large number of patterns can be obtained. Many approaches have been developed to overcome this problem, as objective measures and clustering, which are respectively used to: (i) highlight the potentially interesting knowledge in domain; (ii) structure the domain, organizing the rules in groups that contain, somehow, similar knowledge. However, objective measures don't reduce nor organize the collection of rules, making the understanding of the domain difficult. On the other hand, clustering doesn't reduce the exploration space nor direct the user to find interesting knowledge, making the search for relevant knowledge not so easy. This work proposes the PAR-COM (Post-processing Association Rules with Clustering and Objective Measures) methodology that, combining clustering and objective measures, reduces the association rule exploration space directing the user to what is potentially interesting. Thereby, PAR-COM minimizes the user's effort during the post-processing process.

PAR-COM: A new methodology for post-processing association rules

The post-processing of association rules is a difficult task, since a huge number of rules that are generated are of no interest to the user. To overcome this problem many approaches have been developed, such as objective measures and clustering. However, objective measures don't reduce nor organize the collection of rules, therefore making the understanding of the domain difficult. On the other hand, clustering doesn't reduce the exploration space nor direct the user to find interesting knowledge, therefore making the search for relevant knowledge not so easy. In this context this paper presents the PAR-COM methodology that, by combining clustering and objective measures, reduces the association rule exploration space directing the user to what is potentially interesting. An experimental study demonstrates the potential of PAR-COM to minimize the user's effort during the post-processing process. © 2012 Springer-Verlag.

Unsupervised segmentation method for cuboidal cell nuclei in histological prostate images based on minimum cross entropy

This paper presents a novel segmentation method for cuboidal cell nuclei in images of prostate tissue stained with hematoxylin and eosin. The proposed method allows segmenting normal, hyperplastic and cancerous prostate images in three steps: pre-processing, segmentation of cuboidal cell nuclei and post-processing. The pre-processing step consists of applying contrast stretching to the red (R) channel to highlight the contrast of cuboidal cell nuclei. The aim of the second step is to apply global thresholding based on minimum cross entropy to generate a binary image with candidate regions for cuboidal cell nuclei. In the post-processing step, false positives are removed using the connected component method. The proposed segmentation method was applied to an image bank with 105 samples and measures of sensitivity, specificity and accuracy were compared with those provided by other segmentation approaches available in the specialized literature. The results are promising and demonstrate that the proposed method allows the segmentation of cuboidal cell nuclei with a mean accuracy of 97%. © 2013 Elsevier Ltd. All rights reserved.

Coffee processing residues as a soil potassium amendment

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

Avaliação da influência da angulação dos implantes com diferentes tipos de conexão protética na distribuição de tensões: estudo pelo método dos elementos finitos tridimensionais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise das tensões em próteses unitárias implantossuportadas com diferentes tipos de conexões e qualidade óssea: estudo pelo método dos elementos finitos tridimensionais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Unsupervised manifold learning using Reciprocal kNN Graphs in image re-ranking and rank aggregation tasks

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

An automatic method for segmentation of fission tracks in epidote crystal photomicrographs

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

O impacto do preparo, da cerâmica e do contato oclusal na distribuição de tensões em facetas

Pós-graduação em Odontologia Restauradora - ICT

Análise da distribuição de tensões em reabilitação com implantes cone morse em maxilar posterior: estudo pelo MEF 3D não linear

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

Influência do método de filetagem e categorias de peso sobre rendimento de carcaça, filé e pele da tilápia do Nilo (Oreochromis niloticus)

The objective of this study was to evaluate the processing methods (F-1 = to remove skin with pliers and then to cut in fillets; F-2 = cut in fillet and then to remove skin with knife and pliers help) and weight categories (W-1=250-300 g; W-2=301-350 g; W-3 = 351-400 g and W-4 = 401-450 g), on the carcass (CY), fillet (FY) and skin yield of Nile tilapia. Forty-eight fishes were used in a completely randomized design. There was effect for the processing method, being the F-1 mean (56.43 and 36.67 %) higher to the F-2 (53.46 and 32.89%) for CY and FY respectively. For the weight categories, W-1 (56.49 and 37.34%) and W-2 (56.34 and 36.40%) were superior as compared to W-3 (53.27 and 31.98%) and W-4 (53.71 and 33.42%), respectively for CY and FY. Crude skin percentage, clean and of fleshed were higher for F-2, but there was no effect for weight categories. The F-1 processing method promoted the best yield and skin results, and for the weight categories W-1 and W-2 higher yields.