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Upper limit for context-based crop classification in robotic weeding applications
The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Odense, Denmark.
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
Operations Management, Aarhus University, Tjele, Denmark.
Signal Processing, Aarhus University, Aarhus, Denmark.
2016 (English)In: Biosystems Engineering, ISSN 1537-5110, E-ISSN 1537-5129, Vol. 146, 183-192 p.Article in journal (Refereed) Published
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Text
Abstract [en]

Knowledge of the precise position of crop plants is a prerequisite for effective mechanical weed control in robotic weeding application such as in crops like sugar beets which are sensitive to mechanical stress. Visual detection and recognition of crop plants based on their shapes has been described many times in the literature. In this paper the potential of using knowledge about the crop seed pattern is investigated based on simulated output from a perception system. The reliability of position–based crop plant detection is shown to depend on the weed density (ρ, measured in weed plants per square metre) and the crop plant pattern position uncertainty (σx and σy, measured in metres along and perpendicular to the crop row, respectively). The recognition reliability can be described with the positive predictive value (PPV), which is limited by the seeding pattern uncertainty and the weed density according to the inequality: PPV ≤ (1 + 2πρσxσy)−1. This result matches computer simulations of two novel methods for position–based crop recognition as well as earlier reported field–based trials. © 2016 IAgrE

Place, publisher, year, edition, pages
London: Academic Press, 2016. Vol. 146, 183-192 p.
Keyword [en]
Crop recognition, Row structure, Weeding robots
National Category
Signal Processing Robotics
Identifiers
URN: urn:nbn:se:hh:diva-31234DOI: 10.1016/j.biosystemseng.2016.01.012ISI: 000378966400014Scopus ID: 2-s2.0-84958260860OAI: oai:DiVA.org:hh-31234DiVA: diva2:939043
Note

Special Issue: Advances in Robotic Agriculture for Crops

Available from: 2016-06-17 Created: 2016-06-17 Last updated: 2017-11-30Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • de-DE
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Output format
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