Autoria: SANTOS, T. T.; BASSOI, L. H.; OLDONI, H.; MARTINS, R. L.

Resumo: 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.

Ano de publicação: 2017

Tipo de publicação: Artigo em anais e proceedings

Unidade: Embrapa Agricultura Digital

Palavras-chave: 3-D phenotyping, 3D phenotyping, Estimativa de podução, Fenotipagem 3D, Multiple view stereo, Métodos não-invasivos, Non invasive methods, Non-invasive methods, Phenotype, SLAM, Simultaneous localization and mapping, Videira, Visão estéro múltipla, Viticultura, Yeld estimation, Yield estimation, viticulture