Sensoriamento remoto e geoprocessamento aplicado ao estudo temporal do uso da terra e na comparação entre classificação não supervisionada e análise visual

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

Restauração de imagens digitais com texturas utilizando técnicas de decomposição e equações diferenciais parciais

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

Modelos matemáticos para o retoque digital de imagens

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Implementação em hardware de um sistema inteligente para detecção de plantas daninhas em plantações de soja utilizando máquinas de vetores de suporte e redes neurais artificiais

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Implementação em FPGA de um sistema para processamento de imagens digitais para aplicações diversificadas

Pós-graduação em Ciência da Computação - IBILCE

Processamento de imagens digitais para detecção e quantificação de defeitos na madeira serrada de coníferas de reflorestamento de uso não estrutural

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

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.