Geração automática de modelos digitais de superfícies utilizando múltiplas imagens

Pós-graduação em Ciências Cartográficas - FCT

Sistema de armazenamento de imagens comprimidas através da transformada wavelet

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Segmentação morfológica aplicada à cartografia

Pós-graduação em Ciências Cartográficas - FCT

Análise de multirresolução baseada em polinômio potência de Sigmóide - Wavelet

Pós-graduação em Ciência da Computação - IBILCE

Desenvolvimento de um programa computacional para classificação do uso da terra em imagens CBERS 2

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

A transformada wavelet na fusão de imagens de sensoriamento remoto

Pós-graduação em Matematica Aplicada e Computacional - FCT

Composição de dicionários visuais utilizando agrupamento de dados por Florestas de Caminhos Ótimos

Pós-graduação em Ciência da Computação - IBILCE

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

Pós-graduação em Ciência da Computação - IBILCE

Avaliação da eficiência de dois programas na eliminação de ruído para técnica de subtração

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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.

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.

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

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Image segmentation through combined methods: watershed transform, unsupervised distance learning and normalized cut

Research on image processing has shown that combining segmentation methods may lead to a solid approach to extract semantic information from different sort of images. Within this context, the Normalized Cut (NCut) is usually used as a final partitioning tool for graphs modeled in some chosen method. This work explores the Watershed Transform as a modeling tool, using different criteria of the hierarchical Watershed to convert an image into an adjacency graph. The Watershed is combined with an unsupervised distance learning step that redistributes the graph weights and redefines the Similarity matrix, before the final segmentation step using NCut. Adopting the Berkeley Segmentation Data Set and Benchmark as a background, our goal is to compare the results obtained for this method with previous work to validate its performance.

Ridge-based fingerprint matching using hough transform

Despite the efficacy of minutia-based fingerprint matching techniques for good-quality images captured by optical sensors, minutia-based techniques do not often perform so well on poor-quality images or fingerprint images captured by small solid-state sensors. Solid-state fingerprint sensors are being increasingly deployed in a wide range of applications for user authentication purposes. Therefore, it is necessary to develop new fingerprint-matching techniques that utilize other features to deal with fingerprint images captured by solid-state sensors. This paper presents a new fingerprint matching technique based on fingerprint ridge features. This technique was assessed on the MSU-VERIDICOM database, which consists of fingerprint impressions obtained from 160 users (4 impressions per finger) using a solid-state sensor. The combination of ridge-based matching scores computed by the proposed ridge-based technique with minutia-based matching scores leads to a reduction of the false non-match rate by approximately 1.7% at a false match rate of 0.1%. © 2005 IEEE.

Desenvolvimento de um aplicativo para processamento de imagens obtidas por fotografias aéreas

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