• DocumentCode
    2962255
  • Title

    Identification and Location of Picking Tomatoes Based on Machine Vision

  • Author

    Xiao-lian, Lv ; Xiao-rong, Lv ; Bing-fu, Lu

  • Author_Institution
    Dept. of Electr. & Inf., Chuzhou Coll., Chuzhou, China
  • Volume
    2
  • fYear
    2011
  • fDate
    28-29 March 2011
  • Firstpage
    101
  • Lastpage
    107
  • Abstract
    Through researched the method of the identification and location based on machine vision, location information of mature tomatoes has been obtained, which can be used to guide the automated picking operation of ripe tomatoes. The segmentation of visual system is based on the difference between the color characteristics of ripe tomatoes and background. Through the gray-scale method, the treatment of the color image is turned into gray image processing, and the picking tomatoes is accurately identified using mathematical morphology, object extraction, and region filling methods. Furthermore centroid of picking tomatoes is selected as match features, and the picking tomatoes location information is determined through three-dimensional reconstruction method of space point. The experimental results show that the identification of mature fruit can reach 98%, the green ripe fruit up to 89%, positioning error can be controlled within less than 15 mm, identification and location effects can satisfactorily meet actual work requirements.
  • Keywords
    agricultural products; computer vision; image colour analysis; image reconstruction; image segmentation; production engineering computing; color image treatment; gray image processing; gray-scale method; identification; location information; machine vision; mature fruit; object extraction; region filling methods; three-dimensional reconstruction method; tomatoes; visual system segmentation; Cameras; Equations; Image color analysis; Image segmentation; Mathematical model; Object segmentation; Pixel; centroid matching; color space; identification; location; segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computation Technology and Automation (ICICTA), 2011 International Conference on
  • Conference_Location
    Shenzhen, Guangdong
  • Print_ISBN
    978-1-61284-289-9
  • Type

    conf

  • DOI
    10.1109/ICICTA.2011.316
  • Filename
    5750843