Análise de formas planas em imagens digitais

Given the widespread use of computers, the visual pattern recognition task has been automated in order to address the huge amount of available digital images. Many applications use image processing techniques as well as feature extraction and visual pattern recognition algorithms in order to identify people, to make the disease diagnosis process easier, to classify objects, etc. based on digital images. Among the features that can be extracted and analyzed from images is the shape of objects or regions. In some cases, shape is the unique feature that can be extracted with a relatively high accuracy from the image. In this work we present some of most important shape analysis methods and compare their performance when applied on three well-known shape image databases. Finally, we propose the development of a new shape descriptor based on the Hough Transform.

Análise e aferição de uma fresadora CNC através da utilização das tecnologias assistidas por computador, no escaneamento 3D de amostras e processamento de imagens

The use of computer-assisted technologies such as CAD - Computed Aided Design, CAM - Computed Aided Manufacturing, CAE - Computed Aided Engineering and CNC - Computed Numerical Control, are priorities in engineering and product designers. However, the dimensional measurement between the virtual and the real product design requires research, and dissemination procedures among its users. This work aims to use these technologies, through analysis and measurement of a CNC milling machine, designed and assembled in the university. Through the use of 3D scanning, and analyzing images of the machined samples, and its original virtual files, it was possible to compare the sizes of these samples in counterposition to the original virtual dimensions, we can state that the distortions between the real and virtual, are within acceptable limits for this type of equipment. As a secondary objective, this work seeks to disseminate and make more accessible the use of these technologies.

A ditadura militar revisitada de 10 em 10 anos através de imagens: as fotografias de arquivo e a urdidura das reportagens de rememoração

Since photographic document always bears the marks of a given universe imagined, subject to fi ctionality inherent in all assemblies plot as an act, the purpose of this article is to analyze the photographs archival materials disclosed in remembrance of the Brazilian military dictatorship in the magazine Veja, published in the decennial anniversaries of the 1964 coup, from the methodological assumptions of the rhetoric of image. If, in some cases, archival photographs reinforced the argument of the report, in others, they created a parallel narrative, framing the present through an interpreted past.

Segmentação de imagens utilizando competição e cooperação entre partículas

Este artigo apresenta uma proposta de extensão do modelo de aprendizado semi-supervisionado conhecido como Competição e Cooperação entre Partículas para a realização de tarefas de segmentação de imagens. Resultados preliminares mostram que esta é uma abordagem promissora.

A Revista Criança fala aos professores: imagens de criança e a educação Pré-Escolar

Pós-graduação em Educação Escolar - FCLAR

Estimativa do número de frutos verdes em laranjeiras com o uso de imagens digitais

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Aplicação de técnicas de processamento e análise de imagens para detecção de edificações e vegetação a partir de dados LiDAR

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Imagens e histórias em arte terapia: experiências nas interfaces da psicologia, da educação e da arte

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Imagens das juventudes: uma mirada sobre o comportamento midiático-digital dos jovens de Bauru

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Imagens digitais na análise do uso da terra de uma microbacia como subsídio ao desenvolvimento sustentável

The present work sought to discriminate, to map and to quantify the areas of soil use of the Stream Monte Belo watershed - Botucatu (SP), obtained by digitale images. The cartographic bases were the shart planialtimetric, edited by IBGE (1969) and the satellite images LANDSAT - 7, passages of 21/01/1999, 08/01/2003 and 23/10/2006. The Software Idrisi Andes 15.0 were used for conversion of the analogical information for digital and for determination of the vegetable coverings areas. The results allowed to verify that the SIG - IDRISI Andes 15.0 were efficient in the quantification of the areas with soil use and that the analysis of the data showed a cash progress of the areas of reforestations to the detriment of the areas of pastures, especially from 1999, 2003 to 2006, when the field areas were substituted by the forestry in his totality. In spite of that progress, the forest areas that you correspond to the Permanent Preservation Areas, They are considerably preserved. That result comes to the encounter of the tendency of expansion of the forestry, especially after the installation of cellulose industries in the area, what worsened the environmental problems originating from of the practice of the monoculture.

Imagens aéreas multiespectrais na identificação de zonas de manejo em áreas de algodão para aplicação localizada de insumos

Crop yield is influenced by several factors with variability in time and space that are associated with the variations in the plant vigor. This variability allows the identification of management zones and site-specific applications to manage different regions of the field. The purpose of this study was the use of multispectral image for management zones identification and implications of site-specific application in commercial cotton areas. Multispectral airborne images from three years were used to classify a field into three vegetation classes via the Normalized Difference Vegetation Index (NDVI). The NDVI classes were used to verify the potential differences between plant physical measurements and identify management zones. The cotton plant measurements sampled in 8 repetitions of 10 plants at each NDVI class were Stand Count, Plant Height, Total Nodes and Total Bolls. Statistical analysis was performed with treatments arranged in split plot design with Tukey’s Test at 5% of probability. The images were classified into five NDVI classes to evaluate the relationship between cotton plant measurement results and sampling location across the field. The results have demonstrated the possibility of using multispectral image for management zones identification in cotton areas. The image classification into three NDVI classes showed three different zones in the field with similar characteristics for the studied years. Statistical differences were shown for plant height, total nodes and total bolls between low and high NDVI classes for all years. High NDVI classes contained plants with greater height, total nodes and total bolls compared to low NDVI classes. There was no difference in Stand Count between low and high NDVI classes for the three studied years. The final plant stand was the same between all NDVI classes for 2001 and 2003 as it was expected due to the conventional seeding application with the same rate of seeds for the entire field.

Imagens digitais aplicadas no estudo da análise multitemporal do uso e ocupação do solo numa microbacia

The knowledge of the soil occupation as for his nature, location, occurrence form, changes happened in certain periods, they are valuable for the programming of activities that you seek to the development agricultural, economical and social of the area. This work aimed at to identify and to quantify the soil occupation of Stream Petiço Watershed - Botucatu (SP), through the Geographical Information System IDRISI and data of sensor Landsat 5 TM of 09/06/97 and 23/08/2013. For the analysis of the results it was verified that the eucalyptus culture, due to existence of great reforestation companies in the watershed, together with the native forests they are predominant in the study area, the remaining of the area is occupied by pastures and soil prepared for the planting of agricultural cultures.

Métodos de classificação de imagens na identificação de áreas cultivadas com citros

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Comparação de métodos de classificação de imagens na identificação de áreas cultivadas com citros

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Discriminação de classes de cobertura vegetal utilizando técnicas de classificação digital de imagens de sensoriamento remoto

The aim of this work is to discriminate vegetation classes throught remote sensing images from the satellite CBERS-2, related to winter and summer seasons in the Campos Gerais region Paraná State, Brazil. The vegetation cover of the region presents different kinds of vegetations: summer and winter cultures, reforestation areas, natural areas and pasture. Supervised classification techniques like Maximum Likelihood Classifier (MLC) and Decision Tree were evaluated, considering a set of attributes from images, composed by bands of the CCD sensor (1, 2, 3, 4), vegetation indices (CTVI, DVI, GEMI, NDVI, SR, SAVI, TVI), mixture models (soil, shadow, vegetation) and the two first main components. The evaluation of the classifications accuracy was made using the classification error matrix and the kappa coefficient. It was defined a high discriminatory level during the classes definition, in order to allow separation of different kinds of winter and summer crops. The classification accuracy by decision tree was 94.5% and the kappa coefficient was 0.9389 for the scene 157/128. For the scene 158/127, the values were 88% and 0.8667, respectively. The classification accuracy by MLC was 84.86% and the kappa coefficient was 0.8099 for the scene 157/128. For the scene 158/127, the values were 77.90% and 0.7476, respectively. The results showed a better performance of the Decision Tree classifier than MLC, especially to the classes related to cultivated crops, indicating the use of the Decision Tree classifier to the vegetation cover mapping including different kinds of crops.