Detalhes bibliográficos
| Ano de defesa: |
2016 |
| Autor(a) principal: |
Scortegagna, Lucas Tonial
 |
| Orientador(a): |
Rieder, Rafael
|
| Banca de defesa: |
Não Informado pela instituição |
| Tipo de documento: |
Dissertação
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade de Passo Fundo
|
| Programa de Pós-Graduação: |
Programa de Pós-Graduação em Computação Aplicada
|
| Departamento: |
Instituto de Ciências Exatas e Geociências – ICEG
|
| País: |
BR
|
| 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://10.0.217.128:8080/jspui/handle/tede/20
|
Resumo: |
The aim of this paper is to present a study about image processing applied to Agriculture, the methodology and the development of software named berryIP, in order to detect strawberry flowers. This solution offers the farmers a tool capable of discovering flowers during the process of transition from vegetative to reproductive growth, contributing to a management for high productivity. Our approach analyzes the results of the processing of a pilot study, considering 134 strawberry images, and comparing their performance regarding the manual counting. The success rates and relative errors obtained show reasonable results, and reveal that the application still needs evolution. On the other hand, we observed that this approach is the first step to supply an innovative solution for the strawberry farmers, helping them in decision-making processes |
