Individual plant definition and missing plant characterization in vineyards from high-resolution UAV imagery. Issue 1 (1st January 2017)

• Record Type: Journal Article
• Authors: Primicerio, Jacopo; Caruso, Giovanni; Comba, Lorenzo; Crisci, Alfonso; Gay, Paolo; Guidoni, Silvia; Genesio, Lorenzo; Ricauda Aimonino, Davide; Vaccari, Francesco Primo
• Is Part Of: European journal of remote sensing. Volume 50:Issue 1(2017)
• Page Start: 179
• Page End: 186
• Publication Date: 2017-01-01
• Subjects: Precision viticulture -- UAV -- missing plants -- plant detection -- remote sensing; Remote sensing -- Periodicals; Remote sensing; Electronic journals; Periodicals; 621.3678
• DOI: 10.1080/22797254.2017.1308234
• Languages: English
• ISSNs: 2279-7254

Abstract

ABSTRACT: 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.