Development of a machine vision system for a real time precision sprayer

In the context of precision agriculture, we have developed a machine vision system for a real time precision sprayer. From a monochrome CCD camera located in front of the tractor, the discrimination between crop and weeds is obtained with an image processing based on spatial information using a Gabo...

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Bibliographic Details
Main Authors: Jérémie Bossu, Christelle Gee, Frederic Truchetet
Format: Article
Language:English
Published: Computer Vision Center Press 2008-12-01
Series:ELCVIA Electronic Letters on Computer Vision and Image Analysis
Subjects:
Online Access:https://elcvia.cvc.uab.es/article/view/223
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spelling doaj-c8687a2bfbd44871bf7a33ab75f67c152021-09-18T12:40:26ZengComputer Vision Center PressELCVIA Electronic Letters on Computer Vision and Image Analysis1577-50972008-12-017310.5565/rev/elcvia.223145Development of a machine vision system for a real time precision sprayerJérémie BossuChristelle GeeFrederic TruchetetIn the context of precision agriculture, we have developed a machine vision system for a real time precision sprayer. From a monochrome CCD camera located in front of the tractor, the discrimination between crop and weeds is obtained with an image processing based on spatial information using a Gabor filter. This method allows to detect the periodic signals from the non periodic one and it enables to enhance the crop rows whereas weeds have patchy distribution. Thus, weed patches were clearly identified by a blob-coloring method. Finally, we use a pinhole model to transform the weed patch coordinates image in world coordinates in order to activate the right electro-pneumatic valve of the sprayer at the right moment.https://elcvia.cvc.uab.es/article/view/223Gabor filterimage processingprecision agricultureweedscropspraying
collection DOAJ
language English
format Article
sources DOAJ
author Jérémie Bossu
Christelle Gee
Frederic Truchetet
spellingShingle Jérémie Bossu
Christelle Gee
Frederic Truchetet
Development of a machine vision system for a real time precision sprayer
ELCVIA Electronic Letters on Computer Vision and Image Analysis
Gabor filter
image processing
precision agriculture
weeds
crop
spraying
author_facet Jérémie Bossu
Christelle Gee
Frederic Truchetet
author_sort Jérémie Bossu
title Development of a machine vision system for a real time precision sprayer
title_short Development of a machine vision system for a real time precision sprayer
title_full Development of a machine vision system for a real time precision sprayer
title_fullStr Development of a machine vision system for a real time precision sprayer
title_full_unstemmed Development of a machine vision system for a real time precision sprayer
title_sort development of a machine vision system for a real time precision sprayer
publisher Computer Vision Center Press
series ELCVIA Electronic Letters on Computer Vision and Image Analysis
issn 1577-5097
publishDate 2008-12-01
description In the context of precision agriculture, we have developed a machine vision system for a real time precision sprayer. From a monochrome CCD camera located in front of the tractor, the discrimination between crop and weeds is obtained with an image processing based on spatial information using a Gabor filter. This method allows to detect the periodic signals from the non periodic one and it enables to enhance the crop rows whereas weeds have patchy distribution. Thus, weed patches were clearly identified by a blob-coloring method. Finally, we use a pinhole model to transform the weed patch coordinates image in world coordinates in order to activate the right electro-pneumatic valve of the sprayer at the right moment.
topic Gabor filter
image processing
precision agriculture
weeds
crop
spraying
url https://elcvia.cvc.uab.es/article/view/223
work_keys_str_mv AT jeremiebossu developmentofamachinevisionsystemforarealtimeprecisionsprayer
AT christellegee developmentofamachinevisionsystemforarealtimeprecisionsprayer
AT frederictruchetet developmentofamachinevisionsystemforarealtimeprecisionsprayer
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