ORBi: Piron Alexis - Improving in-row weed detection in multispectral stereoscopic images

Reference : Improving in-row weed detection in multispectral stereoscopic images


	Document type :	Scientific journals : Article
	Discipline(s) :	Life sciences : Environmental sciences & ecology
	To cite this reference:	http://hdl.handle.net/2268/27435

Title :	Improving in-row weed detection in multispectral stereoscopic images
Language :	English
Author, co-author :	Piron, Alexis [Université de Liège - ULg > Gembloux Agro-Bio Tech > Gembloux Agro-Bio Tech >]
	Leemans, Vincent [Université de Liège - ULg > Gembloux Agro-Bio Tech > Gembloux Agro-Bio Tech >]
	Lebeau, Frédéric [Université de Liège - ULg > Gembloux Agro-Bio Tech > Gembloux Agro-Bio Tech >]
	Destain, Marie-France [Université de Liège - ULg > Gembloux Agro-Bio Tech > Gembloux Agro-Bio Tech >]
Publication date :	2009
Journal title :	Computers & Electronics in Agriculture
Publisher :	Elsevier Science
Volume :	69
Pages :	73-79
Audience :	International
ISSN :	0168-1699
Keywords :	[en] stereovision ; multispectral ; weed detection
Abstract :	[en] Previous research has shown that plant height and spectral reflectance are relevant features to classify crop and weeds in organic carrots: classification based on height gave a classification accuracy (CA) of up to 83% while classification based on a combination of three multispectral bands gave a CA of 72%. The first goal of this study was to examine the simultaneous use of both height and multispectral parameters. It was found that classification rate was only slightly improved when using a feature set comprising both height and multispectral data (2%). The second goal of this study was to improve the detection method based on plant height by setting an automatic threshold between crop and weeds heights, in their early growth stage. This threshold was based on crop row determination and peak detection in plant height probability density function, corresponding to the homogeneous crop population. Using this method, the CA was 82% while the CA obtained with optimal plant height limits is only slightly higher at 86%.
Research units :	Gembloux Agro-Bio Tech
Funders :	Région wallonne : Direction générale des Technologies, de la Recherche et de l'Energie - DGTRE
Name of the research project :	RECADVEN
Target :	Researchers
Permalink :	http://hdl.handle.net/2268/27435
DOI :	10.1016/j.compag.2009.07.001
Other URL :	http://reflexions.ulg.ac.be/RobotChamps

File(s) associated to this reference

Fulltext file(s):

	File	Commentary	Version	Size	Access
Open access	Piron A, Compag 2.pdf		Publisher postprint	1.47 MB	View/Open

All documents in ORBi are protected by a user license.

Dspace v1.5