Machine vision guided sensor positioning system for leaf temperature assessment.
A sensor positioning system was developed for monitoring plants' well-being using a non-contact sensor. Image processing algorithms were developed to identify a target region on a plant leaf. A novel algorithm to recover view depth was developed by using a camera equipped with a computer-controlled zoom lens. The methodology has improved depth recovery resolution over a conventional monocular imaging technique. An algorithm was also developed to find a maximum enclosed circle on a leaf surface so the conical field-of-view of an infrared temperature sensor could be filled by the target without peripheral noise. The center of the enclosed circle and the estimated depth were used to define the sensor 3-D location for accurate plant temperature measurement.
Kim
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Department of Agricultural Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA. kim@age.uiuc.edu
Ling
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D000465:Algorithms; D004784:Environmental Monitoring / Q000295:instrumentation*; D005069:Evaluation Studies as Topic; D007091:Image Processing, Computer-Assisted; D021621:Imaging, Three-Dimensional; D010781:Photography; D018515:Plant Leaves / Q000502:physiology*; D012371:Robotics; D013696:Temperature