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A Novel Approach for Weed Type Classification Based on Shape Descriptors and a Fuzzy Decision-Making Method

AutorHerrera Caro, Pedro Javier ; Dorado, José ; Ribeiro Seijas, Ángela
Palabras clavePrecision agriculture
Weed species discrimination
Fuzzy decision making strategy
Colour segmentation
Hu invariant moments
Geometric shape descriptors
Fecha de publicación19-ago-2014
EditorMultidisciplinary Digital Publishing Institute
CitaciónSensors 14(8): 15304-15324 (2014)
ResumenAn 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.
DescripciónThis is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Versión del editorhttp://dx.doi.org/10.3390/s140815304
URIhttp://hdl.handle.net/10261/108888
DOI10.3390/s140815304
ISSN1424-8220
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