Leaves Segmentation in 3D Point Cloud - LAAS - Laboratoire d'Analyse et d'Architecture des Systèmes Accéder directement au contenu
Chapitre D'ouvrage Année : 2017

Leaves Segmentation in 3D Point Cloud

Résumé

This paper presents a 3D plant segmentation method with an emphasis on segmentation of the leaves. This method is part of a 3D plant phenotyping project with a main objective that deals with the development of the leaf area over time. First, a 3D point cloud of a plant is obtained with Structure from Motion technique and the cloud is then segmented into the main components of a plant: the stem and the leaves. As the main objective is to measure leaf area over time, an emphasis was placed on accurate segmentation and the labelling of the leaves. This article presents an original approach which starts by finding the stem in a 3D point cloud and then the leaves. Moreover, this method relies on the model of a plant as well as the agronomic rules to affect a unique label that do not change over time. This method is evaluated using two morphologically distinct plants, sunflower and sorghum.
Fichier principal
Vignette du fichier
paper224.pdf (2.02 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01957617 , version 1 (17-12-2018)

Identifiants

  • HAL Id : hal-01957617 , version 1

Citer

William Gélard, Ariane Herbulot, Michel Devy, Philippe Debaeke, Ryan F Mccormick, et al.. Leaves Segmentation in 3D Point Cloud. Advanced Concepts for Intelligent Vision Systems 18th International Conference, ACIVS 2017, Antwerp, Belgium, September 18-21, 2017, Proceedings, pp.664-674, 2017. ⟨hal-01957617⟩
43 Consultations
19 Téléchargements

Partager

Gmail Facebook X LinkedIn More