Fruit size and leaf area are important indicators for plant health and are of interest for plant nutrient management, plant protection and harvest. In this research, an image-based method for measuring the fruit volume as well as the leaf area for cabbage is presented. For this purpose, a mask region-based convolutional neural network (Mask R-CNN) was trained to segment the cabbage fruit from the leaves and assign it to the corresponding plant. The results indicated that even with a single camera, the developed method can provide a calculation accuracy of fruit size of 92.6% and an accuracy of leaf area of 89.8% on individual plant level.
@article{arxiv.2104.05284,
title = {Volume and leaf area calculation of cabbage with a neural network-based instance segmentation},
author = {Nils Lueling and David Reiser and Hans W. Griepentrog},
journal= {arXiv preprint arXiv:2104.05284},
year = {2021}
}