• DocumentCode
    2779204
  • Title

    A fruit recognition method for automatic harvesting

  • Author

    Yang, L. ; Dickinson, J. ; Wu, Q.M.J. ; Lang, S.

  • Author_Institution
    Windsor Univ., Windsor
  • fYear
    2007
  • fDate
    4-6 Dec. 2007
  • Firstpage
    152
  • Lastpage
    157
  • Abstract
    This paper presents a method to detect and recognize mature tomato fruit clusters on a complex-structured tomato plant containing clutter and occlusion in a tomato greenhouse for automatic harvesting purpose. A color stereo vision camera (PGR BumbleBee2) is applied as the vision sensor. The proposed method performs a 3D reconstruction with the data collected by the stereo camera to create a 3D environment for further processing. The color layer growing (CLG) method is introduced to segment the mature fruits from the leaves, stalks, background and noise. Target fruit clusters can then be located by depth segmentation. The experimental data was collected from a tomato greenhouse and the method is justified by the experimental results. Our experiments included severe self and stereo occlusion, which wasn´t both included in the previous work.
  • Keywords
    agricultural engineering; agricultural products; greenhouses; image colour analysis; image recognition; image segmentation; object detection; stereo image processing; PGR BumbleBee2; automatic harvesting; clutter; color layer growing; color stereo vision camera; fruit detection; fruit recognition; fruit segmentation; mature tomato fruit clusters; stereo occlusion; tomato greenhouse; tomato plant; vision sensor; Automation; Cameras; Colored noise; Costs; Filters; Image edge detection; Image reconstruction; Robot vision systems; Shape; Smoothing methods; 3D Reconstruction; Color Segmentation; Fruit Recognition; Object Localization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechatronics and Machine Vision in Practice, 2007. M2VIP 2007. 14th International Conference on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-1-4244-1358-4
  • Electronic_ISBN
    978-1-4244-1358-4
  • Type

    conf

  • DOI
    10.1109/MMVIP.2007.4430734
  • Filename
    4430734