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Individual plant definition and missing plant characterization in vineyards from high-resolution UAV imagery

By Jacopo Primicerio, Giovanni Caruso, Lorenzo Comba, Alfonso Crisci, Paolo Gay, Silvia Guidoni, Lorenzo Genesio, Davide Ricauda Aimonino and Francesco Primo Vaccari


In the last few years, high-resolution imaging of vineyards, obtained by unmanned aerial vehicle recognitions, has provided new opportunities to obtain valuable information for precision farming applications. While available semi-automatic image processing algorithms are now able to detect parcels and extract vine rows from aerial images, the identification of single plant inside the rows is a problem still unaddressed. This study presents a new methodology for the segmentation of vine rows in virtual shapes, each representing a real plant. From the virtual shapes, an extensive set of features is discussed, extracted and coupled to a statistical classifier, to evaluate its performance in missing plant detection within a vineyard parcel. Passing from continuous images to a discrete set of individual plants results in a crucial simplification of the statistical investigation of the problem

Topics: Precision viticulture, UAV, missing plants, plant detection, remote sensing, Oceanography, GC1-1581, Geology, QE1-996.5
Publisher: Taylor & Francis Group
Year: 2017
DOI identifier: 10.1080/22797254.2017.1308234
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