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Ponencias en congresos:
A Comparison of Fuzzy Clustering Algorithms Applied to Feature Extraction on Vineyard
Año:2011
Áreas de investigación
  • Agricultura,
  • Robótica
Datos
Descripción
Image segmentation is a process by which an image is partitioned into regions with similar features. Many approaches have been proposed for color image segmentation, but Fuzzy C-Means has been widely used, because it has a good performance in a large class of images. However, it is not adequate for noisy images and it also takes more time for execution as compared to other method as K-means. For this reason, several methods have been proposed to improve these weaknesses. Method like Possibilistic C-Means, Fuzzy Possibilistic C-Means, Robust Fuzzy Possibilistic C-Means and Fuzzy C-Means with Gustafson-Kessel algorithm. In this paper we perform a comparison of these clustering algorithms applied to feature extraction on vineyard images. Segmented images are evaluated using several quality parameters such as the rate of correctly classied area and runtime
Internacional
No
Nombre congreso
The Conference of the Spanish Association for Artificial Intelligence
Tipo de participación
960
Lugar del congreso
San Cristobal de La Laguna. Tenerife
Revisores
Si
ISBN o ISSN
DOI
Fecha inicio congreso
06/11/2011
Fecha fin congreso
11/11/2011
Desde la página
0
Hasta la página
10
Título de las actas
Avances en inteligencia artificial
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Christian Correa Farias (UPM)
  • Autor: Pilar Barreiro Elorza (UPM)
  • Autor: Constantino Valero Ubierna (UPM)
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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