Title:	Automatic grape bunch detection in vineyards based on affordable 3D phenotyping using a consumer webcam.
Authors:	SANTOS, T. T. BASSOI, L. H. OLDONI, H. MARTINS, R. L.
Affiliation:	THIAGO TEIXEIRA SANTOS, CNPTIA; LUIS HENRIQUE BASSOI, CNPDIA; HENRIQUE OLDONI, Unesp Botucatu; ROBERTO LUVISUTTO MARTINS, Unesp Botucatu.
Date Issued:	2017
Citation:	In: CONGRESSO BRASILEIRO DE AGROINFORMÁTICA, 11., 2017, Campinas. Ciência de dados na era da agricultura digital: anais. Campinas: Editora da Unicamp: Embrapa Informática Agropecuária, 2017.
Pages:	p. 89-98.
Description:	This work presents a methodology for 3-D phenotyping of vineyards based on images captured by a low cost high-definition webcamera. A novel software application integrated visual odometry and multiple-view stereo components to create dense and accurate three-dimensional points clouds for vines, properly transformed to millimeter scale. Geometrical and color features of the points were employed by a classification procedure that reached 93% of accuracy on detecting points belonging to grapes. Individual bunches were automatically delimited and their volumes estimated. The sum of the estimated volumes per vine presented a coefficient of correlation of R = 0.99 to the real grape weight observed in each vine after harvesting.
Thesagro:	Viticultura
NAL Thesaurus:	Viticulture Phenotype
Keywords:	Estimativa de podução Métodos não-invasivos Fenotipagem 3D Visão estéro múltipla Simultaneous localization and mapping Yield estimation Non-invasive methods 3-D phenotyping Multiple view stereo Videira
ISBN:	978-85-85783-75-4
Notes:	SBIAgro 2017.
Type of Material:	Artigo em anais e proceedings
Access:	openAccess
Appears in Collections:	Artigo em anais de congresso (CNPTIA)