A computer vision approach for weeds identification through Support Vector Machines

Tellaeche, Alberto; Pajares, Gonzalo; Burgos Artizzu, Xavier y Ribeiro Seijas, Ángela (2011). A computer vision approach for weeds identification through Support Vector Machines. "Applied Soft Computing Journal", v. 11 (n. 1); pp. 908-915. ISSN 15684946. https://doi.org/10.1016/j.asoc.2010.01.011.

Descripción

Título: A computer vision approach for weeds identification through Support Vector Machines
Autor/es:
  • Tellaeche, Alberto
  • Pajares, Gonzalo
  • Burgos Artizzu, Xavier
  • Ribeiro Seijas, Ángela
Tipo de Documento: Artículo
Título de Revista/Publicación: Applied Soft Computing Journal
Fecha: Enero 2011
Volumen: 11
Materias:
Escuela: Otros Centros UPM
Departamento: Otro
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

This paper outlines an automatic computervision system for the identification of avena sterilis which is a special weed seed growing in cereal crops. The final goal is to reduce the quantity of herbicide to be sprayed as an important and necessary step for precision agriculture. So, only areas where the presence of weeds is important should be sprayed. The main problems for the identification of this kind of weed are its similar spectral signature with respect the crops and also its irregular distribution in the field. It has been designed a new strategy involving two processes: image segmentation and decision making. The image segmentation combines basic suitable image processing techniques in order to extract cells from the image as the low level units. Each cell is described by two area-based attributes measuring the relations among the crops and weeds. The decision making is based on the SupportVectorMachines and determines if a cell must be sprayed. The main findings of this paper are reflected in the combination of the segmentation and the SupportVectorMachines decision processes. Another important contribution of this approach is the minimum requirements of the system in terms of memory and computation power if compared with other previous works. The performance of the method is illustrated by comparative analysis against some existing strategies.

Más información

ID de Registro: 13714
Identificador DC: http://oa.upm.es/13714/
Identificador OAI: oai:oa.upm.es:13714
Identificador DOI: 10.1016/j.asoc.2010.01.011
Depositado por: Memoria Investigacion
Depositado el: 20 Nov 2012 09:13
Ultima Modificación: 24 Feb 2017 17:49
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