Recursive hierarchic segmentation analysis of bone mineral density changes on digital panoramic images

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Effects of meal size and proximal-distal segmentation on gastric activity

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

Independent and interactive effects of a top and an intermediate fish species on the food web structure of a tropical stream

Two fish species, one top predator (Imparfinis mirini) and one intermediate detritivorous species (Hisonotus depressicauda), were experimentally manipulated to evaluate their relative importance in structuring the periphytic community, as well as their effects on the other trophic levels. An enclosure experiment was conducted in the Potreirinho creek, a second order tributary of Paranapanema River, SE Brazil. Five treatments were used: enclosure of the predator species. enclosure of the detritivorous species, enclosure of both together, exclusion of all fish species (closed control cage), and cage open to all fish community, (open control). Through direct and indirect effects, I. mirini, when alone gave rise to a trophic cascade that resulted in a positive effect on algal resources. Through direct effects, H. depressicauda. when alone, reduced the amount of organic matter, resulting in a positive indirect effect on algae. In addition, when the two species were enclosed together, only the effects determined by the detritivorous species were present. The results indicate the important role of the intermediate detritivorous species in the maintenance of the composition and trophic structure of the analyzed community by reducing the effects caused by the top predator.

An interactive environment for solid modeling based on free software

This paper describes an interactive environment built entirely upon public domain or free software, intended to be used as the preprocessor of a finite element package for the simulation of three-dimensional electromagnetic problems.

Anatomicosurgical arterial segmentation of the cat lungs (Felis catus domesticus, L., 1758)

O objetivo desta pesquisa foi estabelecer os segmentos anátomo-cirúrgicos arteriais, através da lobação e ramificação intralobar arterial, em pulmões de gato. Após a dissecção de vinte pulmões, notou-se que a artéria pulmonar direita geralmente emite um ramo para o lobo cranial e um ramo para o lobo médio, sendo originados juntos em um tronco. Um grande ramo irriga o lobo caudal na maioria dos casos. Dois ramos com origem comum no ramo arterial do lobo caudal irrigam o lobo acessório. A artéria pulmonar esquerda origina um tronco que, na maioria dos casos, emite um ramo para a porção cranial e um ramo para a porção caudal do lobo cranial esquerdo. Pode-se concluir que o pulmão direito é formado por quatro e o esquerdo por dois lobos, ocorrendo variações na ramificação arterial pulmonar.

A method for the digital image analysis of ceramic grains based on shape factor segmentation

A very simple and robust method for ceramics grains quantitative image analysis is presented. Based on the use of optimal imaging conditions for reflective light microscopy of bulk samples, a digital image processing routine was developed for shading correction, noise suppressing and contours enhancement. Image analysis was done for grains selected according to their concavities, evaluated by perimeter ratio shape factor, to avoid consider the effects of breakouts and ghost boundaries due to ceramographic preparation limitations. As an example, the method was applied for two ceramics, to compare grain size and morphology distributions. In this case, most of artefacts introduced by ceramographic preparation could be discarded due to the use of perimeter ratio exclusion range.

Interactive system for placement and coordination of overcurrent protective devices

In this paper, an expert and interactive system for developing protection system for overhead and radial distribution feeders is proposed. In this system the protective devices can be allocated through heuristic and an optimized way. In the latter one, the placement problem is modeled as a mixed integer non-linear programming, which is solved by genetic algorithm (GA). Using information stored in a database as well as a knowledge base, the computational system is able to obtain excellent conditions of selectivity and coordination for improving the feeder reliability indices. Tests for assessment of the algorithm efficiency were carried out using a real-life 660-nodes feeder. © 2006 IEEE.

JSEG-based image segmentation in computer vision for agricultural mobile robot navigation

This project aims to apply image processing techniques in computer vision featuring an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained.

Interactive DC-DC converters tools for instant design and education

This paper deals with the usage of interactive simulations tools to serve as an oriented design tool for the lectures and laboratory experiments in the power electronics courses. A dynamic and interactive visualization of simulations for idealized converters in steady state are provided by the proposed educational tools, allowing students to acquire qualification in non-isolated DC-DC converters, without previous circuitry knowledge, either without the usage of sophisticated simulation packages. The interaction with proposed simulation tools can be accomplished by student using direct or graphic mode. In direct mode the parameters related with the design of converter can be inserted simply editing default values presented in textboxes, while in the graphic mode students interact indirectly with design information by manipulating visual widgets. In order to corroborate the proposed interactive simulation tools, comparisons of results from buck-boost and boost converters on proposed tools and a well-known simulator package with those on experimental evaluation from laboratory classes were presented. © 2009 IEEE.

Fast automatic microstructural segmentation of ferrous alloy samples using optimum-path forest

In this work we propose a novel automatic cast iron segmentation approach based on the Optimum-Path Forest classifier (OPF). Microscopic images from nodular, gray and malleable cast irons are segmented using OPF, and Support Vector Machines (SVM) with Radial Basis Function and SVM without kernel mapping. Results show accurate and fast segmented images, in which OPF outperformed SVMs. Our work is the first into applying OPF for automatic cast iron segmentation. © 2010 Springer-Verlag.

Automatic segmentation of digital images applied in cardiac medical images

The digital image processing has been applied in several areas, especially where it is necessary use tools for feature extraction and to get patterns of the studied images. In an initial stage, the segmentation is used to separate the image in parts that represents a interest object, that may be used in a specific study. There are several methods that intends to perform such task, but is difficult to find a method that can easily adapt to different type of images, that often are very complex or specific. To resolve this problem, this project aims to presents a adaptable segmentation method, that can be applied to different type of images, providing an better segmentation. The proposed method is based in a model of automatic multilevel thresholding and considers techniques of group histogram quantization, analysis of the histogram slope percentage and calculation of maximum entropy to define the threshold. The technique was applied to segment the cell core and potential rejection of tissue in myocardial images of biopsies from cardiac transplant. The results are significant in comparison with those provided by one of the best known segmentation methods available in the literature. © 2010 IEEE.

Precipitates segmentation from scanning electron microscope images through machine learning techniques

The presence of precipitates in metallic materials affects its durability, resistance and mechanical properties. Hence, its automatic identification by image processing and machine learning techniques may lead to reliable and efficient assessments on the materials. In this paper, we introduce four widely used supervised pattern recognition techniques to accomplish metallic precipitates segmentation in scanning electron microscope images from dissimilar welding on a Hastelloy C-276 alloy: Support Vector Machines, Optimum-Path Forest, Self Organizing Maps and a Bayesian classifier. Experimental results demonstrated that all classifiers achieved similar recognition rates with good results validated by an expert in metallographic image analysis. © 2011 Springer-Verlag Berlin Heidelberg.

Automatic segmentation of the secondary austenite-phase island precipitates in a superduplex stainless steel weld metal

Duplex and superduplex stainless steels are class of materials of a high importance for engineering purposes, since they have good mechanical properties combination and also are very resistant to corrosion. It is known as well that the chemical composition of such steels is very important to maintain some desired properties. In the past years, some works have reported that γ 2 precipitation improves the toughness of such steels, and its quantification may reveals some important information about steel quality. Thus, we propose in this work the automatic segmentation of γ 2 precipitation using two pattern recognition techniques: Optimum-Path Forest (OPF) and a Bayesian classifier. To the best of our knowledge, this if the first time that machine learning techniques are applied into this area. The experimental results showed that both techniques achieved similar and good recognition rates. © 2012 Taylor & Francis Group.

Semiautomatic dental recognition using a graph-based segmentation algorithm and teeth shapes features

Dental recognition is very important for forensic human identification, mainly regarding the mass disasters, which have frequently happened due to tsunamis, airplanes crashes, etc. Algorithms for automatic, precise, and robust teeth segmentation from radiograph images are crucial for dental recognition. In this work we propose the use of a graph-based algorithm to extract the teeth contours from panoramic dental radiographs that are used as dental features. In order to assess our proposal, we have carried out experiments using a database of 1126 tooth images, obtained from 40 panoramic dental radiograph images from 20 individuals. The results of the graph-based algorithm was qualitatively assessed by a human expert who reported excellent scores. For dental recognition we propose the use of the teeth shapes as biometric features, by the means of BAS (Bean Angle Statistics) and Shape Context descriptors. The BAS descriptors showed, on the same database, a better performance (EER 14%) than the Shape Context (EER 20%). © 2012 IEEE.