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Memorias de investigación
Communications at congresses:
Row Crop's Identication Through Hough Transform using Images Segmented by Robust Fuzzy Possibilistic C-MeansCharacterization of vineyard's canopy through fuzzy clustering and svm over color images
Year:2011
Research Areas
  • Agriculture
Information
Abstract
The Hough transform (HT) is a widely used method for line detection and recognition, due to its robustness. But its performance is strongly dependent on the applied segmentation technique. On the other hand, Fuzzy C-Means (FCM) has been widely used in image segmenta- tion because it has a good performance in a large class of images. How- ever, it is not good for noisy images, so that to overcome this weakness several modi?cations to FCM have been proposed, like Robust Fuzzy Possibilistic C-Means (RFPCM). In this paper, we propose to use the RFPCM algorithm for the segmentation of crops images in order to ap- ply the HT to detect lines in row crops for navigation purposes. The proposed method gives better results compared with techniques based on visible spectral-index or Speci?c threshold-based approaches. No hay ISBN
International
No
Congress
Conference of the Spanish Association for Artificial Intelligence (CAEPIA 2011)
960
Place
San Cristobal de la laguna. Tenerife
Reviewers
Si
ISBN/ISSN
0000000000000
Start Date
07/11/2011
End Date
10/11/2011
From page
1
To page
10
Conference of the Spanish Association for Artificial Intelligence (CAEPIA)
Participants
  • Autor: Christian Correa Farias (UPM)
  • Autor: Constantino Valero Ubierna (UPM)
  • Autor: Pilar Barreiro Elorza (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: LPF-TAGRALIA: Técnicas Avanzadas en Agroalimentación
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Cofinanciación del MINECO en el marco del Programa INNCIDE 2011 (OTR-2011-0236)
Cofinanciación del MINECO en el marco del Programa INNPACTO (IPT-020000-2010-22)