René Gislum

Segmentation of lettuce in coloured 3D point clouds for fresh weight estimation

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

  • Anders Krogh Mortensen
  • Asher Bender, Australian Centre for Field Robotics, Sydney University, Australia
  • Brett Whelan, Sydney Institute of Agriculture, The University of Sydney, Australia
  • Margaret M. Barbour, Sydney Institute of Agriculture, The University of Sydney, Australia
  • Salah Sukkarieh, Australian Centre for Field Robotics, Sydney University, Australia
  • Henrik Karstoft
  • René Gislum
Monitoring the health and yield of crops during production is an important, but labour intensive component of commercial agriculture, especially in high value crop such as lettuce. This article proposes a novel method for segmenting lettuce in coloured 3D point clouds and estimating the fresh weight. The proposed segmentation method operates by clustering points into leaves and then evaluating their affiliation to a lettuce of interest. From the segmented lettuce point clouds, the volume, surface area, leaf cover area and height predictors are extracted and correlated to the fresh weight. The proposed segmentation and yield estimation methods are evaluated on Cos and Iceberg lettuce point clouds generated from images collected by an agricultural robot in an outdoor field experiment. The results demonstrate that the proposed segmentation method is able to successfully isolate lettuce (F1-score = 0.88–0.91). Analysis of the segmented lettuce models show that the calculated surface areas correlate strongly with measured fresh weight (R^2 = 0.84–0.94). Not only does this validate the segmentation method, it allows an accurate estimate of the lettuce fresh weight (RMSE = 27–50 g) to be produced non-destructively.
Original languageEnglish
JournalComputers and Electronics in Agriculture
Volume154
Pages (from-to)373-381
Number of pages9
ISSN0168-1699
DOIs
Publication statusPublished - Nov 2018

    Research areas

  • leafy vegetables, Photogrammetry, Structure from motion, Biomass, Computer vision, Agricultural robotics

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