Uma abordagem híbrida e semiautomática para estimativa de regiões cobertas por nuvens e sombras em imagens de satélite: análise e avaliação

Os principais objetivos deste trabalho são propor um algoritmo eficiente e o mais automático possível para estimar o que está coberto por regiões de nuvens e sombras em imagens de satélite; e um índice de confiabilidade, que seja aplicado previamente à imagem, visando medir a viabilidade da estimação das regiões cobertas pelos componentes atmosféricos usando tal algoritmo. A motivação vem dos problemas causados por esses elementos, entre eles: dificultam a identificação de objetos de imagem, prejudicam o monitoramento urbano e ambiental, e desfavorecem etapas cruciais do processamento digital de imagens para extrair informações ao usuário, como segmentação e classificação. Através de uma abordagem híbrida, é proposto um método para decompor regiões usando um filtro passa-baixas não-linear de mediana, a fim de mapear as regiões de estrutura (homogêneas), como vegetação, e de textura (heterogêneas), como áreas urbanas, na imagem. Nessas áreas, foram aplicados os métodos de restauração Inpainting por suavização baseado em Transformada Cosseno Discreta (DCT), e Síntese de Textura baseada em modelos, respectivamente. É importante salientar que as técnicas foram modificadas para serem capazes de trabalhar com imagens de características peculiares que são obtidas por meio de sensores de satélite, como por exemplo, as grandes dimensões e a alta variação espectral. Já o índice de confiabilidade, tem como objetivo analisar a imagem que contém as interferências atmosféricas e daí estimar o quão confiável será a redefinição com base no percentual de cobertura de nuvens sobre as regiões de textura e estrutura. Tal índice é composto pela combinação do resultado de algoritmos supervisionados e não-supervisionados envolvendo 3 métricas: Exatidão Global Média (EGM), Medida De Similaridade Estrutural (SSIM) e Confiança Média Dos Pixels (CM). Finalmente, verificou-se a eficácia destas metodologias através de uma avaliação quantitativa (proporcionada pelo índice) e qualitativa (pelas imagens resultantes do processamento), mostrando ser possível a aplicação das técnicas para solucionar os problemas que motivaram a realização deste trabalho.

Avaliação de uma técnica para geração de modelos digitais de superfície utilizando múltiplas imagens

The efficient generation of digital surface model (DSM) from optical images has been explored for many years and the results are dependent on the project characteristics (image resolution, size of overlap between images, among others), of the image matching techniques and the computer capabilities for the image processing. The points generated from image matching have a direct impact on the quality of the DSM and, consequently, influence the need for the costly step of edition. This work aims at assessing experimentally a technique for DSM generation by matching of multiple images (two or more) simultaneously using the vertical line locus method (VLL). The experiments were performed with six images of the urban area of Presidente Prudente/SP, with a ground sample distance (GSD) of approximately 7cm. DSMs of a small area with homogeneous texture, repetitive pattern, moving objects including shadows and trees were generated to assess the quality of the developed procedure. This obtained DSM was compared to cloud points acquired by LASER (Light Amplification by Simulated Emission of Radiation) scanning as wells as with a DSM generated by Leica Photogrammetric Suite (LPS) software. The accomplished results showed that the MDS generated by the implemented technique has a geometric quality compatible with the reference models.

Restauração de imagens utilizando projeções em conjuntos convexos e algoritmos evolucionistas

Pós-graduação em Ciência da Computação - IBILCE

Análise de formas planas em imagens digitais: uma nova abordagem baseada na Transformada de Hough

Pós-graduação em Ciência da Computação - IBILCE

Medidas de deslocamento e vibrações através de imagens de câmeras digitais

Pós-graduação em Engenharia Mecânica - FEIS

Application of two segmentation protocols during the processing of virtual images in rapid prototyping: ex vivo study with human dry mandibles

The aim of this study was to evaluate the accuracy of virtual three-dimensional (3D) reconstructions of human dry mandibles, produced from two segmentation protocols (outline only and all-boundary lines).Twenty virtual three-dimensional (3D) images were built from computed tomography exam (CT) of 10 dry mandibles, in which linear measurements between anatomical landmarks were obtained and compared to an error probability of 5 %.The results showed no statistically significant difference among the dry mandibles and the virtual 3D reconstructions produced from segmentation protocols tested (p = 0,24).During the designing of a virtual 3D reconstruction, both outline only and all-boundary lines segmentation protocols can be used.Virtual processing of CT images is the most complex stage during the manufacture of the biomodel. Establishing a better protocol during this phase allows the construction of a biomodel with characteristics that are closer to the original anatomical structures. This is essential to ensure a correct preoperative planning and a suitable treatment.

Machine vision to identify broiler breeder behavior

Animal behavioral parameters can be used to assess welfare status in commercial broiler breeders. Behavioral parameters can be monitored with a variety of sensing devices, for instance, the use of video cameras allows comprehensive assessment of animal behavioral expressions. Nevertheless, the development of efficient methods and algorithms to continuously identify and differentiate animal behavior patterns is needed. The objective this study was to provide a methodology to identify hen white broiler breeder behavior using combined techniques of image processing and computer vision. These techniques were applied to differentiate body shapes from a sequence of frames as the birds expressed their behaviors. The method was comprised of four stages: (1) identification of body positions and their relationship with typical behaviors. For this stage, the number of frames required to identify each behavior was determined; (2) collection of image samples, with the isolation of the birds that expressed a behavior of interest; (3) image processing and analysis using a filter developed to separate white birds from the dark background; and finally (4) construction and validation of a behavioral classification tree, using the software tool Weka (model 148). The constructed tree was structured in 8 levels and 27 leaves, and it was validated using two modes: the set training mode with an overall rate of success of 96.7%, and the cross validation mode with an overall rate of success of 70.3%. The results presented here confirmed the feasibility of the method developed to identify white broiler breeder behavior for a particular group of study. Nevertheless, more improvements in the method can be made in order to increase the validation overall rate of success. (C) 2013 Elsevier B.V. All rights reserved.

Classificação de tábuas de madeira usando processamento de imagens digitais e aprendizado de máquina

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Estimating the concentration of gold nanoparticles incorporated on natural rubber membranes using multi-level starlet optimal segmentation

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

Automatic visual dictionary generation through optimum-path forest clusteringautomatic visual dictionary generation through optimum-path forest clustering

Image categorization by means of bag of visual words has received increasing attention by the image processing and vision communities in the last years. In these approaches, each image is represented by invariant points of interest which are mapped to a Hilbert Space representing a visual dictionary which aims at comprising the most discriminative features in a set of images. Notwithstanding, the main problem of such approaches is to find a compact and representative dictionary. Finding such representative dictionary automatically with no user intervention is an even more difficult task. In this paper, we propose a method to automatically find such dictionary by employing a recent developed graph-based clustering algorithm called Optimum-Path Forest, which does not make any assumption about the visual dictionary's size and is more efficient and effective than the state-of-the-art techniques used for dictionary generation.

Utilização de geotecnologias no monitoramento de processos erosivos e movimentos de massa em trecho da faixa de dutos Rio de Janeiro - Belo Horizonte

The transportation of oil through pipelines raises a concern related to safety and environmental impacts they may cause, especially when exposed to risks that affect their integrity. Among the natural phenomena that can affect the pipelines are erosion and landslides. Considering the large territory involving the pipelines, remote sensing tools have a great applicability for data acquisition. For this, visual analysis techniques were applied to perform change detection in order to monitor erosion features and landslides along a stretch of pipeline Rio de Janeiro – Belo Horizonte, in the state of Rio de Janeiro. The work involved the characterization of the study area as well as the erosion and landslide processes, through bibliographical data. The satellite image processing and the application of change detection techniques were developed in two scenes for the years 2002 and 2010. It was noted a small increase in the number of the identified features, however with regard to their area, a decrease of 21.7% was observed

Avaliação do método de classificação baseada no objeto em imagens de alta resolução espacial aplicado para o monitoramento de faixa de dutos: estudo de caso no entorno da refinaria de Capuava em Mauá - SP

The metropolitan region of São Paulo is the most populous of the country, this happens because of its great importance in the national economy and the job opportunities that are offered to the population. These factors result in intense population growth and urban expansion, reaching some non-habitable places of the metropolis, as areas of pipelines, which are very important for the transportation of natural gas, oil and its derivatives. Before the population growth of the region, these sites were unoccupied, do not presenting problems for the population. However, with the disorderly occupation is generated great anthropogenic pressure on the pipeline stitches, causing risks to people who are around them. Therefore it is extremely important to monitor the strip of pipelines through products and techniques of remote sensing and geoprocessing, enabling, through high spatial resolution images, identification of objects or phenomena that occur on Earth's surface that can alter the functioning and safety of pipelines. Therefore, this study aims to monitor a stretch of the area of the pipeline mesh GASPAL/OSVAT and Capuava Refinery (RECAP), located on the outskirts of the metropolitan area of São Paulo in the city of Mauá, who suffer great human pressure, proving thus the techniques of remote sensing and geographic information system (GIS) as effective tools for monitoring phenomena occurred in urban areas of great complexity. The monitoring was done by object-based classification applied in orbital images Ikonos II and RapidEye, of high spatial resolution and, image processing, detection of objects, segmentation, classification and editing were developed through the eCognition and ArcGis softwares. To determine the statistical accuracy of the mapping of the land cover of the stretch of pipeline in Maua, the results were analyzed by error matrix... (Complete abstract click electronic access below)

Análise de regiões em cenários agrícolas utilizando um sistema de visão catadióptrico

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Inserção e extração de marca d'água em imagens digitais usando a transformada wavelet

Pós-graduação em Engenharia Elétrica - FEIS

Desenvolvimento do sistema computacional CARTOMORPH para processamento de imagens de sensoriamento remoto

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