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Drones, Volume 7, Issue 2
February 2023 - 82 articles
Cover Story: We propose a fully automatic approach to overcome not only individual maize extraction but also the trait quantification challenge of structural components from unmanned aerial system (UAS) imagery. For that, two flights were performed over maize trials using a camera onboard a UAS platform. RGB images were processed using a standard photogrammetric pipeline to obtain a final scaled 3D point cloud. Individual plants were extracted using deep learning. Next, we employed a connected component algorithm to the maize endmembers. Finally, we robustly applied a Laplacian-based contraction skeleton algorithm to compute several structural component traits from each plant. Our test trial reveals the viability of computing 3D phenotypic traits of maize on the basis of a UAS imagery-based point cloud. View this paper
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Drones - ISSN 2504-446XCreative Common CC BY license