Image matching and classification for UAV navigation.
Autor(a) principal: | |
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Data de Publicação: | 2010 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Biblioteca Digital de Teses e Dissertações do ITA |
Texto Completo: | http://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=1077 |
Resumo: | Unmanned aerial vehicles, known as UAVs, have evolved over the past two decades to sophisticated aircraft robots able to carry out surveillance, recognition, remote sensing and even attack missions. But there are not many alternatives of autonomous navigation systems for most of these aircraft which still require human intervention to navigate. Devices such as Global Positioning System (GPS) and inertial systems help calculate routes and locate the vehicle on a map among other possibilities, but do not offer solutions to unknown or uncertain circumstances. On the other hand, computer vision techniques have provided many possible applications for intelligent systems such as object recognition, robot localization and reconstruction of 3D maps. This paper explores the use of computer vision and pattern recognition techniques for UAV navigation, and proposes a set of visual features based on color and gradients orientation for image classification. To validate the proposed approach, a system was developed to evaluate the classification and matching of aerial images. The results achieve more than 95% of accuracy and confirm the viability of the selected algorithms and methods for the problem. |
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Biblioteca Digital de Teses e Dissertações do ITA |
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Image matching and classification for UAV navigation.Técnicas de formação de imagensAeronave não-tripuladaReconhecimento de padrõesAnálise de imagens coloridasClassificação de imagensCasamento de imagensVisão por computadoresEngenharia eletrônicaUnmanned aerial vehicles, known as UAVs, have evolved over the past two decades to sophisticated aircraft robots able to carry out surveillance, recognition, remote sensing and even attack missions. But there are not many alternatives of autonomous navigation systems for most of these aircraft which still require human intervention to navigate. Devices such as Global Positioning System (GPS) and inertial systems help calculate routes and locate the vehicle on a map among other possibilities, but do not offer solutions to unknown or uncertain circumstances. On the other hand, computer vision techniques have provided many possible applications for intelligent systems such as object recognition, robot localization and reconstruction of 3D maps. This paper explores the use of computer vision and pattern recognition techniques for UAV navigation, and proposes a set of visual features based on color and gradients orientation for image classification. To validate the proposed approach, a system was developed to evaluate the classification and matching of aerial images. The results achieve more than 95% of accuracy and confirm the viability of the selected algorithms and methods for the problem.Instituto Tecnológico de AeronáuticaSérgio Roberto Matiello PellegrinoRicardo Cezar Bonfim Rodrigues2010-11-17info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesishttp://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=1077reponame:Biblioteca Digital de Teses e Dissertações do ITAinstname:Instituto Tecnológico de Aeronáuticainstacron:ITAenginfo:eu-repo/semantics/openAccessapplication/pdf2019-02-02T14:02:03Zoai:agregador.ibict.br.BDTD_ITA:oai:ita.br:1077http://oai.bdtd.ibict.br/requestopendoar:null2020-05-28 19:35:10.247Biblioteca Digital de Teses e Dissertações do ITA - Instituto Tecnológico de Aeronáuticatrue |
dc.title.none.fl_str_mv |
Image matching and classification for UAV navigation. |
title |
Image matching and classification for UAV navigation. |
spellingShingle |
Image matching and classification for UAV navigation. Ricardo Cezar Bonfim Rodrigues Técnicas de formação de imagens Aeronave não-tripulada Reconhecimento de padrões Análise de imagens coloridas Classificação de imagens Casamento de imagens Visão por computadores Engenharia eletrônica |
title_short |
Image matching and classification for UAV navigation. |
title_full |
Image matching and classification for UAV navigation. |
title_fullStr |
Image matching and classification for UAV navigation. |
title_full_unstemmed |
Image matching and classification for UAV navigation. |
title_sort |
Image matching and classification for UAV navigation. |
author |
Ricardo Cezar Bonfim Rodrigues |
author_facet |
Ricardo Cezar Bonfim Rodrigues |
author_role |
author |
dc.contributor.none.fl_str_mv |
Sérgio Roberto Matiello Pellegrino |
dc.contributor.author.fl_str_mv |
Ricardo Cezar Bonfim Rodrigues |
dc.subject.por.fl_str_mv |
Técnicas de formação de imagens Aeronave não-tripulada Reconhecimento de padrões Análise de imagens coloridas Classificação de imagens Casamento de imagens Visão por computadores Engenharia eletrônica |
topic |
Técnicas de formação de imagens Aeronave não-tripulada Reconhecimento de padrões Análise de imagens coloridas Classificação de imagens Casamento de imagens Visão por computadores Engenharia eletrônica |
dc.description.none.fl_txt_mv |
Unmanned aerial vehicles, known as UAVs, have evolved over the past two decades to sophisticated aircraft robots able to carry out surveillance, recognition, remote sensing and even attack missions. But there are not many alternatives of autonomous navigation systems for most of these aircraft which still require human intervention to navigate. Devices such as Global Positioning System (GPS) and inertial systems help calculate routes and locate the vehicle on a map among other possibilities, but do not offer solutions to unknown or uncertain circumstances. On the other hand, computer vision techniques have provided many possible applications for intelligent systems such as object recognition, robot localization and reconstruction of 3D maps. This paper explores the use of computer vision and pattern recognition techniques for UAV navigation, and proposes a set of visual features based on color and gradients orientation for image classification. To validate the proposed approach, a system was developed to evaluate the classification and matching of aerial images. The results achieve more than 95% of accuracy and confirm the viability of the selected algorithms and methods for the problem. |
description |
Unmanned aerial vehicles, known as UAVs, have evolved over the past two decades to sophisticated aircraft robots able to carry out surveillance, recognition, remote sensing and even attack missions. But there are not many alternatives of autonomous navigation systems for most of these aircraft which still require human intervention to navigate. Devices such as Global Positioning System (GPS) and inertial systems help calculate routes and locate the vehicle on a map among other possibilities, but do not offer solutions to unknown or uncertain circumstances. On the other hand, computer vision techniques have provided many possible applications for intelligent systems such as object recognition, robot localization and reconstruction of 3D maps. This paper explores the use of computer vision and pattern recognition techniques for UAV navigation, and proposes a set of visual features based on color and gradients orientation for image classification. To validate the proposed approach, a system was developed to evaluate the classification and matching of aerial images. The results achieve more than 95% of accuracy and confirm the viability of the selected algorithms and methods for the problem. |
publishDate |
2010 |
dc.date.none.fl_str_mv |
2010-11-17 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/masterThesis |
status_str |
publishedVersion |
format |
masterThesis |
dc.identifier.uri.fl_str_mv |
http://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=1077 |
url |
http://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=1077 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Instituto Tecnológico de Aeronáutica |
publisher.none.fl_str_mv |
Instituto Tecnológico de Aeronáutica |
dc.source.none.fl_str_mv |
reponame:Biblioteca Digital de Teses e Dissertações do ITA instname:Instituto Tecnológico de Aeronáutica instacron:ITA |
reponame_str |
Biblioteca Digital de Teses e Dissertações do ITA |
collection |
Biblioteca Digital de Teses e Dissertações do ITA |
instname_str |
Instituto Tecnológico de Aeronáutica |
instacron_str |
ITA |
institution |
ITA |
repository.name.fl_str_mv |
Biblioteca Digital de Teses e Dissertações do ITA - Instituto Tecnológico de Aeronáutica |
repository.mail.fl_str_mv |
|
subject_por_txtF_mv |
Técnicas de formação de imagens Aeronave não-tripulada Reconhecimento de padrões Análise de imagens coloridas Classificação de imagens Casamento de imagens Visão por computadores Engenharia eletrônica |
_version_ |
1706809265588535296 |