Open Access

Spatial and Spectral Methods for Weed Detection and Localization

  • Jean-Baptiste Vioix1Email author,
  • Jean-Paul Douzals1,
  • Frédéric Truchetet2,
  • Louis Assémat3 and
  • Jean-Philippe Guillemin4
EURASIP Journal on Advances in Signal Processing20022002:793080

https://doi.org/10.1155/S1110865702204072

Received: 26 July 2001

Published: 24 July 2002

Abstract

This study concerns the detection and localization of weed patches in order to improve the knowledge on weed-crop competition. A remote control aircraft provided with a camera allowed to obtain low cost and repetitive information. Different processings were involved to detect weed patches using spatial then spectral methods. First, a shift of colorimetric base allowed to separate the soil and plant pixels. Then, a specific algorithm including Gabor filter was applied to detect crop rows on the vegetation image. Weed patches were then deduced from the comparison of vegetation and crop images. Finally, the development of a multispectral acquisition device is introduced. First results for the discrimination of weeds and crops using the spectral properties are shown from laboratory tests. Application of neural networks were mostly studied.

Keywords

weed detection spatial analysis spectral analysis Gabor filter neural network image processing

Authors’ Affiliations

(1)
UMR CPAP ENESAD CEMAGREF
(2)
Le2i, IUT Le Creusot
(3)
INRA, Unité de Malherbologie et Agronomie
(4)
ENESAD laboratoire CBF

Copyright

© Vioix et al. 2002