AmandaBoatswain/cv-based-yield-monitor

Code developed for my Masters thesis project. A machine vision-based yield monitor was designed to perform identification, size categorization and continuous counting of shallot onions in-situ during the harvesting process. The system is composed of a video logger and global positioning system (GPS), coupled with computer software developed in Python. Computer vision analysis is performed within the tractor itself while an RGB camera positioned directly above the harvesting conveyor collects real time video data of the crops under natural sunlight conditions. Vegetables are segmented using Watershed segmentation, detected on the conveyor and then classified by size.

语言：Python · GitHub 星标：9 · Fork：0

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