Agricultural plant cataloging and establishment of a data framework from UAV-based crop images by computer vision.

ABSTRACT:

Background

Unmanned aerial vehicle (UAV)-based image retrieval in modern agriculture enables gathering large amounts of spatially referenced crop image data. In large-scale experiments, however, UAV images suffer from containing a multitudinous amount of crops in a complex canopy architecture. Especially for the observation of temporal effects, this complicates the recognition of individual plants over several images and the extraction of relevant information tremendously.

Results

In this work, we present a hands-on workflow for the automatized temporal and spatial identification and individualization of crop images from UAVs abbreviated as "cataloging" based on comprehensible computer vision methods. We evaluate the workflow on 2 real-world datasets. One dataset is recorded

SUBMITTER: Gunder M 

PROVIDER: S-EPMC9205758 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature