Mango Fruit Load Estimation Using a Video Based MangoYOLO-Kalman Filter-Hungarian Algorithm Method.

ABSTRACT: : Pre-harvest fruit yield estimation is useful to guide harvesting and marketing resourcing, but machine vision estimates based on a single view from each side of the tree ("dual-view") underestimates the fruit yield as fruit can be hidden from view. A method is proposed involving deep learning, Kalman filter, and Hungarian algorithm for on-tree mango fruit detection, tracking, and counting from 10 frame-per-second videos captured of trees from a platform moving along the inter row at 5 km/h. The deep learning based mango fruit detection algorithm, MangoYOLO, was used to detect fruit in each frame. The Hungarian algorithm was used to correlate fruit between neighbouring frames, with the improvement of enabling multiple-to-one assignment. The Kalman filter was used to predict the position o

SUBMITTER: Wang Z 

PROVIDER: S-EPMC6631562 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature