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

Received: 26 July 2001

Published: 24 July 2002


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.


weed detectionspatial analysisspectral analysisGabor filterneural networkimage processing

Authors’ Affiliations

Le2i, IUT Le Creusot, Le Creusot, France
INRA, Unité de Malherbologie et Agronomie, Dijon, France
ENESAD laboratoire CBF, Quetigny, France


© Vioix et al. 2002