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Memorias de investigación
Artículos en revistas:
Grapevine Yield and Leaf Area Estimation Using Supervised Classification Methodology on RGB Images Taken under Field Conditions
Año:2012
Áreas de investigación
  • Tecnología de alimentos
Datos
Descripción
The aim of this research was to implement a methodology through the generation of a supervised classifier based on the Mahalanobis distance to characterize the grapevine canopy and assess leaf area and yield using RGB images. The method automatically processes sets of images, and calculates the areas (number of pixels) corresponding to seven different classes (Grapes, Wood, Background, and four classes of Leaf, of increasing leaf age). Each one is initialized by the user, who selects a set of representative pixels for every class in order to induce the clustering around them. The proposed methodology was evaluated with 70 grapevine (V. vinifera L. cv. Tempranillo) images, acquired in a commercial vineyard located in La Rioja (Spain), after several defoliation and de-fruiting events on 10 vines, with a conventional RGB camera and no artificial illumination. The segmentation results showed a performance of 92% for leaves and 98% for clusters, and allowed to assess the grapevine?s leaf area and yield with R2 values of 0.81 (p < 0.001) and 0.73 (p = 0.002), respectively. This methodology, which operates with a simple image acquisition setup and guarantees the right number and kind of pixel classes, has shown to be suitable and robust enough to provide valuable information for vineyard management.
Internacional
Si
JCR del ISI
Si
Título de la revista
Sensors
ISSN
1424-8220
Factor de impacto JCR
1,739
Información de impacto
Volumen
12
DOI
10.3390/s121216988
Número de revista
12
Desde la página
16988
Hasta la página
17006;
Mes
SIN MES
Ranking
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Christian Correa Farias (UPM)
  • Autor: Pilar Barreiro Elorza (UPM)
  • Autor: Constantino Valero Ubierna (UPM)
  • Autor: María Paz Diago (Instituto de Ciencias de la Vid y del Vino (CSIC, University of La Rioja,)
  • Autor: Borja Millan (Instituto de Ciencias de la Vid y del Vino (CSIC, University of La Rioja))
  • Autor: Javier Tardaguila (Instituto de Ciencias de la Vid y del Vino (CSIC, University of La Rioja,)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: LPF-TAGRALIA: Técnicas Avanzadas en Agroalimentación
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