A Novel Approach for Weed Type Classification Based on Shape Descriptors and a Fuzzy Decision-Making Method
An important objective in weed management is the discrimination between grasses (monocots) and broad-leaved weeds (dicots), because these two weed groups can be appropriately controlled by specific herbicides. In fact, efficiency is higher if selective treatment is performed for each type of infesta...
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Online Access: | http://www.mdpi.com/1424-8220/14/8/15304 |
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doaj-b33e0cba8d9a46bb87a5e27cb16eca762020-11-24T22:17:23ZengMDPI AGSensors1424-82202014-08-01148153041532410.3390/s140815304s140815304A Novel Approach for Weed Type Classification Based on Shape Descriptors and a Fuzzy Decision-Making MethodPedro Javier Herrera0José Dorado1Ángela Ribeiro2Centre for Automation and Robotics, CSIC-UPM, 28500 Madrid, SpainInstitute of Agricultural Sciences, CSIC, 28006 Madrid, SpainCentre for Automation and Robotics, CSIC-UPM, 28500 Madrid, SpainAn important objective in weed management is the discrimination between grasses (monocots) and broad-leaved weeds (dicots), because these two weed groups can be appropriately controlled by specific herbicides. In fact, efficiency is higher if selective treatment is performed for each type of infestation instead of using a broadcast herbicide on the whole surface. This work proposes a strategy where weeds are characterised by a set of shape descriptors (the seven Hu moments and six geometric shape descriptors). Weeds appear in outdoor field images which display real situations obtained from a RGB camera. Thus, images present a mixture of both weed species under varying conditions of lighting. In the presented approach, four decision-making methods were adapted to use the best shape descriptors as attributes and a choice was taken. This proposal establishes a novel methodology with a high success rate in weed species discrimination.http://www.mdpi.com/1424-8220/14/8/15304precision agricultureweed species discriminationfuzzy decision making strategycolour segmentationHu invariant momentsgeometric shape descriptors |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Pedro Javier Herrera José Dorado Ángela Ribeiro |
spellingShingle |
Pedro Javier Herrera José Dorado Ángela Ribeiro A Novel Approach for Weed Type Classification Based on Shape Descriptors and a Fuzzy Decision-Making Method Sensors precision agriculture weed species discrimination fuzzy decision making strategy colour segmentation Hu invariant moments geometric shape descriptors |
author_facet |
Pedro Javier Herrera José Dorado Ángela Ribeiro |
author_sort |
Pedro Javier Herrera |
title |
A Novel Approach for Weed Type Classification Based on Shape Descriptors and a Fuzzy Decision-Making Method |
title_short |
A Novel Approach for Weed Type Classification Based on Shape Descriptors and a Fuzzy Decision-Making Method |
title_full |
A Novel Approach for Weed Type Classification Based on Shape Descriptors and a Fuzzy Decision-Making Method |
title_fullStr |
A Novel Approach for Weed Type Classification Based on Shape Descriptors and a Fuzzy Decision-Making Method |
title_full_unstemmed |
A Novel Approach for Weed Type Classification Based on Shape Descriptors and a Fuzzy Decision-Making Method |
title_sort |
novel approach for weed type classification based on shape descriptors and a fuzzy decision-making method |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2014-08-01 |
description |
An important objective in weed management is the discrimination between grasses (monocots) and broad-leaved weeds (dicots), because these two weed groups can be appropriately controlled by specific herbicides. In fact, efficiency is higher if selective treatment is performed for each type of infestation instead of using a broadcast herbicide on the whole surface. This work proposes a strategy where weeds are characterised by a set of shape descriptors (the seven Hu moments and six geometric shape descriptors). Weeds appear in outdoor field images which display real situations obtained from a RGB camera. Thus, images present a mixture of both weed species under varying conditions of lighting. In the presented approach, four decision-making methods were adapted to use the best shape descriptors as attributes and a choice was taken. This proposal establishes a novel methodology with a high success rate in weed species discrimination. |
topic |
precision agriculture weed species discrimination fuzzy decision making strategy colour segmentation Hu invariant moments geometric shape descriptors |
url |
http://www.mdpi.com/1424-8220/14/8/15304 |
work_keys_str_mv |
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1725784943561277440 |