Memorias de investigación
Artículos en revistas:
Automatic segmentation of relevant textures in agricultural images
Año:2011
Áreas de investigación
  • Ingeniería eléctrica, electrónica y automática
Datos
Descripción
One important issue emerging strongly in agriculture is related with the automatization of tasks, where the optical sensors play an important role. They provide images that must be conveniently processed. The most relevant image processing procedures require the identi?cation of green plants, in our experiments they come from barley and corn crops including weeds, so that some types of action can be carried out, including site-speci?c treatments with chemical products or mechanical manipulations. Also the identi?cation of textures belonging to the soil could be useful to know some variables, such as humidity, smoothness or any others. Finally, from the point of view of the autonomous robot navigation, where the robot is equipped with the imaging system, some times it is convenient to know not only the soil information and the plants growing in the soil but also additional information supplied by global references based on speci?c areas. This implies that the images to be processed contain textures of three main types to be identi?ed: green plants, soil and sky if any. This paper proposes a new automatic approach for segmenting these main textures and also to re?ne the identi?cation of sub-textures inside the main ones. Concerning the green identi?cation, we propose a new approach that exploits the performance of existing strategies by combining them. The combination takes into account the relevance of the information provided by each strategy based on the intensity variability. This makes an important contribution. The combination of thresholding approaches, for segmenting the soil and the sky, makes the second contribution; ?nally the adjusting of the supervised fuzzy clustering approach for identifying sub-textures automatically, makes the third ?nding. The performance of the method allows to verify its viability for automatic tasks in agriculture based on image processing.
Internacional
No
JCR del ISI
No
Título de la revista
Computers and Electronics in Agriculture
ISSN
01681699
Factor de impacto JCR
Información de impacto
Volumen
75
DOI
10.1016/j.compag.2010.09.013
Número de revista
Desde la página
75
Hasta la página
83
Mes
SIN MES
Ranking
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: M. Guijarro CSIC
  • Autor: G. Pajares CSIC
  • Autor: I. Riomoros
  • Autor: P.J. Herrera CSIC
  • Autor: X.P. Burgos-Artizzu CSIC
  • Autor: Angela Ribeiro Seijas UPM
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Centro o Instituto I+D+i: Centro de Automática y Robótica (CAR). Centro Mixto UPM-CSIC