Design of a computer vision system for a differential spraying operation in precision agriculture using Hebbian learning

Author(s): G. Pajares ; A. Tellaeche ; X.-P. BurgosArtizzu ; A. Ribeiro
DOI: 10.1049/iet-cvi:20070028

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Author(s): G. Pajares ¹ ; A. Tellaeche ² ; X.-P. BurgosArtizzu ³ ; A. Ribeiro ³
- Affiliations: 1: Department of Ingeniería del Software e Inteligencia Artificial, Facultad Informática, Universidad Complutense, Madrid, Spain
  2: Department of Informática y Automática, E.T.S. Informática - UNED, Madrid, Spain
  3: Department of Informática y Automática, Instituto de Automática Industrial, CSIC, Arganda del Rey, Madrid, Spain
Source: Volume 1, Issue 3-4, December 2007, p. 93 – 99
DOI: 10.1049/iet-cvi:20070028 , Print ISSN 1751-9632, Online ISSN 1751-9640

One objective in precision agriculture is to minimise the volume of herbicides that are applied to the fields through the use of site-specific weed management systems. An automatic computer vision system for the detection and differential spraying of weeds in crop fields is discussed. The system involves an image segmentation approach and a decision maker. The first is designed as a sequence of image processing techniques and the second is a decision maker based on the Hebbian learning paradigm under the self-organising criterion. The combination of both and the use of the second are the main findings. The method is compared favourably with other existing strategies achieving a suitable performance.

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Design of a computer vision system for a differential spraying operation in precision agriculture using Hebbian learning

Design of a computer vision system for a differential spraying operation in precision agriculture using Hebbian learning

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