Detalhes bibliográficos
| Ano de defesa: |
2016 |
| Autor(a) principal: |
Lima, Heuber Gustavo Frazao de
 |
| Orientador(a): |
Costa, Ronaldo Martins da
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| Banca de defesa: |
Soares, Fabrízzio Alphonsus Alves de Melo Nunes,
Pires, Sandrerley Ramos |
| Tipo de documento: |
Dissertação
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| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Federal de Goiás
|
| Programa de Pós-Graduação: |
Programa de Pós-graduação em Ciência da Computação (INF)
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| Departamento: |
Instituto de Informática - INF (RG)
|
| País: |
Brasil
|
| Palavras-chave em Português: |
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| Palavras-chave em Inglês: |
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| Área do conhecimento CNPq: |
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| Link de acesso: |
http://repositorio.bc.ufg.br/tede/handle/tede/6768
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Resumo: |
The electrical distribution is a critical activity since many people depend of this service. Faults in the distribution system occur from several factors that can damage the system and therefore interrupt the supply of energy. Among the various factors that may cause problems this work proposes a automatic detection of trees near or even in the distribution network. In order to avoid that the trees to force or even rupture of the distribution cables, are made the pruning of the trees that have some kind of risk to the network. However, this activity is usually manual and teams must sift through all the network for problems. The main objective of this work is to propose a process, based on computer vision, which allows the automated identification of nearby trees or under the power distribution network from aerial images provided by Google Earth and even estimate the height of the same from 2D Google Street View images. |
