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A New Combined Strategy for Discrimination between Types of Weed

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ROBOT2013: First Iberian Robotics Conference

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 252))

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Abstract

Specific weed management consists on adjusting herbicide treatments depending on the zone infested and the type of weed. In this context, the discrimination between grasses (monocots) and broad-leaved weeds (dicots) is an important objective mainly because the two weed groups can be appropriately controlled by different specific herbicides. This work proposes a method of discrimination between these types of weeds based on a combined strategy, the Sugeno Fuzzy Integral, where the final decision is taken by combining seven attributes, the Hu moments. The main challenge in terms of image analysis is to achieve an appropriate discrimination between both groups in outdoor field images under varying conditions of lighting as well as of soil background texture.

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Author information

Authors and Affiliations

  1. Centre for Automation and Robotics, CSIC-UPM, 28500, Madrid, Spain

    P. Javier Herrera & Ángela Ribeiro

  2. Institute of Agricultural Sciences, CSIC, 28006, Madrid, Spain

    José Dorado

Authors
  1. P. Javier Herrera
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  2. José Dorado
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  3. Ángela Ribeiro
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Corresponding author

Correspondence to P. Javier Herrera .

Editor information

Editors and Affiliations

  1. CAR UPM-CSIC, State Agency National Research Council (CSIC), Arganda del Rey, Spain

    Manuel A. Armada

  2. University Technical of Catalonia (UPC), Barcelona, Spain

    Alberto Sanfeliu

  3. University Polytechnic of Madrid (UPM), Madrid, Spain

    Manuel Ferre

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Herrera, P.J., Dorado, J., Ribeiro, Á. (2014). A New Combined Strategy for Discrimination between Types of Weed. In: Armada, M., Sanfeliu, A., Ferre, M. (eds) ROBOT2013: First Iberian Robotics Conference. Advances in Intelligent Systems and Computing, vol 252. Springer, Cham. https://doi.org/10.1007/978-3-319-03413-3_34

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  • DOI: https://doi.org/10.1007/978-3-319-03413-3_34

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-03412-6

  • Online ISBN: 978-3-319-03413-3

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