Automatic green fruit counting in orange trees using digital images

Página do item simplificado
dc.contributor.authorMaldonado, Walter [UNESP]
dc.contributor.authorBarbosa, José Carlos [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2018-12-11T17:04:33Z
dc.date.available2018-12-11T17:04:33Z
dc.date.issued2016-09-01
dc.description.abstractYield estimation is an important factor in a production process planning. In the case of citrus crops, can be useful in industrial management and as guidance for farmers, showing a decisive role in the product market strategies and cultivation practices. Several techniques are being studied for estimating citrus crop yield. On the basis of the known correlation between the number of visible fruits in a digital image and the total of fruits present in an orange tree, we developed a method for green fruit feature extraction with a combination of the techniques of color model conversion, thresholding, histogram equalization, spatial filtering with Laplace and Sobel operators and Gaussian blur. In addition, we built and tested an algorithm to recognize and count them, with detection rates of false-positives of 3% in images acquired in good conditions. It is possible to estimate the mean number of visible fruits in the trees within a tolerated error of 5% with up to 46 images and taking approximately 8 min without any human interaction.en
dc.description.affiliationDepartment of Exact Sciences College of Agricultural and Veterinarian Sciences Sao Paulo State University (FCAV/UNESP) Brazil's Citrus Defense Fund (FUNDECITRUS), Via de Acesso Prof. Paulo Donato Castellane, s/n, Jaboticabal
dc.description.affiliationDepartment of Exact Sciences College of Agricultural and Veterinarian Sciences Sao Paulo State University (FCAV/UNESP), Via de Acesso Prof. Paulo Donato Castellane, s/n, Jaboticabal
dc.description.affiliationUnespDepartment of Exact Sciences College of Agricultural and Veterinarian Sciences Sao Paulo State University (FCAV/UNESP) Brazil's Citrus Defense Fund (FUNDECITRUS), Via de Acesso Prof. Paulo Donato Castellane, s/n, Jaboticabal
dc.description.affiliationUnespDepartment of Exact Sciences College of Agricultural and Veterinarian Sciences Sao Paulo State University (FCAV/UNESP), Via de Acesso Prof. Paulo Donato Castellane, s/n, Jaboticabal
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.description.sponsorshipIdCNPq: 140600/2013-2
dc.format.extent572-581
dc.identifierhttp://dx.doi.org/10.1016/j.compag.2016.07.023
dc.identifier.citationComputers and Electronics in Agriculture, v. 127, p. 572-581.
dc.identifier.doi10.1016/j.compag.2016.07.023
dc.identifier.file2-s2.0-84979521121.pdf
dc.identifier.issn0168-1699
dc.identifier.scopus2-s2.0-84979521121
dc.identifier.urihttp://hdl.handle.net/11449/173296
dc.language.isoeng
dc.relation.ispartofComputers and Electronics in Agriculture
dc.relation.ispartofsjr0,814
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectCitrus
dc.subjectComputer vision
dc.subjectFruit detection
dc.subjectPrecision agriculture
dc.subjectYield estimation
dc.titleAutomatic green fruit counting in orange trees using digital imagesen
dc.typeArtigo

Arquivos

Pacote Original
Agora exibindo 1 - 1 de 1
Imagem de Miniatura
Nome:
2-s2.0-84979521121.pdf
Tamanho:
2.29 MB
Formato:
Adobe Portable Document Format
Descrição:
Baixar

Coleções

Artigos - Ciências Exatas - FCAV