• DocumentCode
    2918791
  • Title

    Extraction of Litchi Stem Based on Computer Vision under Natural Scene

  • Author

    Deng, Jizhong ; Li, Jiao ; Zou, Xiangjun

  • Author_Institution
    Key Lab. of Key Technol. on Agric. Machine & Equip., South China Agric. Univ., Guangzhou, China
  • fYear
    2011
  • fDate
    19-20 Feb. 2011
  • Firstpage
    832
  • Lastpage
    835
  • Abstract
    The aim of the litchi stem extraction based on computer vision is to provide the basic image for the position of litchi plucking point. In this paper, the litchi stem extraction was studied by comparing various color models and combining with the cluster segmentation algorithm under natural scene. For the complex natural scene, three steps were taken to finish the litchi stem extraction. Firstly, the image of string-like litchi fruits was extracted through the Cr component in YCbCr color model; Secondly, the image of litchi fruits was extracted from the color image by K-means clustering method which based on RGB; finally, the image of litchi stem was obtained by the image subtraction operation and morphological processing. The results showed that the success rate of stem extraction is 80% by experimenting thirty images collected under natural scene.
  • Keywords
    agricultural products; computer vision; image colour analysis; image segmentation; pattern clustering; production engineering computing; K-means clustering method; RGB; YCbCr color model; cluster segmentation algorithm; computer vision; image subtraction operation; litchi plucking point position; litchi stem extraction; morphological processing; natural scene; Computers; Distributed control; Monitoring; Color Model; Computer Vision; Litchi; Nature Scene; Plucking Point; Stem;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Distributed Control and Intelligent Environmental Monitoring (CDCIEM), 2011 International Conference on
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-61284-278-3
  • Electronic_ISBN
    978-0-7695-4350-5
  • Type

    conf

  • DOI
    10.1109/CDCIEM.2011.380
  • Filename
    5747943