• DocumentCode
    2363599
  • Title

    Classification of Bidens in Wheat Farms

  • Author

    Zhang, Zhenhao ; Kodagoda, Sarath ; Ruiz, Daniel ; Katupitiya, Jayantha ; Dissanayake, Gamini

  • Author_Institution
    ARC Centre of Excellence for Autonomous Syst. (CAS), Univ. of Technol., Sydney, NSW
  • fYear
    2008
  • fDate
    2-4 Dec. 2008
  • Firstpage
    505
  • Lastpage
    510
  • Abstract
    Bidens pilosa L (commonly known as cobbler´s peg) is an annual broad leaf weed widely distributed in tropical and subtropical regions of the world and is reported to be a weed of 31 crops including wheat. Automatic detection of Bidens in wheat farms is a nontrivial problem due to their similarity in color and presence of occlusions. This paper proposes a methodology which could be used to discriminate Bidens from wheat to be used in operations such as autonomous weed destruction. A spectrometer is used to analyze the optical properties of Bidens and wheat leaves while achieving high classification results. However, due to the practical constraints of using spectrometers, a color camera based technique is proposed. It is shown that the color based segmentation followed by shape based validation algorithm gives rise to high detection rates with lower false detections. We have experimentally evaluated the algorithm with Bidens detection rate of 80% and a 10% false alarm rate.
  • Keywords
    crops; image colour analysis; image segmentation; image sensors; object detection; pattern classification; Bidens pilosa L classification; color based segmentation; color camera based technique; wheat farms; Australia; Cameras; Content addressable storage; Costs; Crops; Linear discriminant analysis; Machine vision; Reflectivity; Shape; Spectroscopy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechatronics and Machine Vision in Practice, 2008. M2VIP 2008. 15th International Conference on
  • Conference_Location
    Auckland
  • Print_ISBN
    978-1-4244-3779-5
  • Electronic_ISBN
    978-0-473-13532-4
  • Type

    conf

  • DOI
    10.1109/MMVIP.2008.4749584
  • Filename
    4749584