Automatic grape bunch detection in vineyards based on affordable 3D phenotyping using a consumer webcam

by Thiago Teixeira Santos, Luı́s Henrique Bassoi, Henrique Oldoni and Roberto Luvisutto Martins

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.

Best Paper – XI Congresso Brasileiro de Agroinformática (SBIAgro 2017)

Full-paper at ResearchGate


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