Fruit size information through the season is an important parameter allowing growers to better manage the orchard. In this study, a Python based computer vision algorithm for sizing apples directly on-the-tree was developed. The system was made of a consumer-grade depth camera and tested at two distances and different timings through the season, in a Fuji apple orchard. The system exploited a YOLOv5 detection algorithm and a trigonometric approach based on depth information to size the fruits. Results showed potential field application even if a further system improvement to reduce the sizing error (RMSE <10 mm) need to be achieved.
Bortolotti, G., Gullino, M., Piani, M., Mengoli, D., Manfrini, L. (2023). 67. Apple fruit sizing through low-cost depth camera and neural network application [10.3920/978-90-8686-947-3_67].
67. Apple fruit sizing through low-cost depth camera and neural network application
Bortolotti, G.
Primo
;Gullino, M.;Piani, M.;Mengoli, D.;Manfrini, L.Ultimo
2023
Abstract
Fruit size information through the season is an important parameter allowing growers to better manage the orchard. In this study, a Python based computer vision algorithm for sizing apples directly on-the-tree was developed. The system was made of a consumer-grade depth camera and tested at two distances and different timings through the season, in a Fuji apple orchard. The system exploited a YOLOv5 detection algorithm and a trigonometric approach based on depth information to size the fruits. Results showed potential field application even if a further system improvement to reduce the sizing error (RMSE <10 mm) need to be achieved.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
