WILTING DETECTION IN GREENHOUSE PLANTS BY IMAGE PROCESSING

In this study an algorithm was developed to analyse lateral images of different plants in a model greenhouse.
Images were taken automatically at user defined rime scale, 60 minutes.
A region of interest (ROI) can be selected by the user, in this case a single leaf on the upper-middle of the plant was the Top ROI, a part of the bottom area where leaves were moving in and out from the frame was the Bottom ROI, and a Whole ROI containing a big part of the canopy from the top area to the bottom area was selected.
This way the upper and bottom area of the plant and a bigger area including the Top and Bottom ROI were monitored.
The top and the bottom part of the plant were outside the image.
Canopy direction in degrees, compare to horizontal direction was calculated from the Whole ROI by a method described in the study.
The closest point to the ground (bottom point) among the recognised edge pixels of the canopy was recorded in the Top ROI along with the bottom point of the Bottom ROI. The bottom point of the Top and Bottom ROI among with the canopy direction of the Whole ROI was calculated and stored for each image.
The algorithm compared the measured canopy direction in the Whole ROI to a user defined value after each measurement.
If the measured direction was closer to the vertical direction then the defined value, an irrigation pump was turned on for a user defined time, to water the plants.
In this study tomato was used as a test plant.

International Symposium on High Technology for Greenhouse System Management: Greensys2007

L. Font, I. Farkas

image analysis, machine vision, wellness, stress, wilting, irrigation, automation

https://doi.org/10.17660/ActaHortic.2008.801.77