• DocumentCode
    116252
  • Title

    Study of variable spray control system based on machine vision

  • Author

    Rui Zhang ; Lepeng Song

  • Author_Institution
    Coll. of Electr. & Inf. Eng., Chongqing Univ. of Sci. & Technol., Chongqing, China
  • fYear
    2014
  • fDate
    18-20 Aug. 2014
  • Firstpage
    455
  • Lastpage
    458
  • Abstract
    This system captures and analyses the growth of crops based on machine vision technology, controlled by the PLC variables and achieve the objective of saving fertilizer, improving economic efficiency and protecting the environment. It uses shape or texture of the crops and background information contained in the image to classify, builds database algorithms, processes the collecting real-time signal by the internal computer and provides a spray flow rate required by the target area of operation, thus achieves variable spray to the target automatically. As a result, the real-time database of the precision agriculture variable spray is created; the system then receives the target spray flow signals on the intelligent platform and variable sprays with an intelligent spray operation platform speed.
  • Keywords
    computer vision; crops; environmental factors; fertilisers; image classification; image texture; precision engineering; programmable controllers; shape recognition; sprays; PLC variables; crop growth analysis; crop shape; crop texture; economic efficiency; environment protection; fertilizer saving; image classification; intelligent spray operation platform speed; machine vision; machine vision technology; precision agriculture variable spray; real-time database; real-time signal; spray flow rate; variable spray control system; Agriculture; Computers; Control systems; Image segmentation; Machine vision; Real-time systems; Valves; machine vision; precision agriculture; variable spray;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cognitive Informatics & Cognitive Computing (ICCI*CC), 2014 IEEE 13th International Conference on
  • Conference_Location
    London
  • Print_ISBN
    978-1-4799-6080-4
  • Type

    conf

  • DOI
    10.1109/ICCI-CC.2014.6921498
  • Filename
    6921498