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Thesis - University Access Only
Master of Science (MS)
Department / School
Daniel S. Humburg
A machine vision system was designed, built and calibrated to locate mushrooms on a tray for harvesting. This system was designed to reduce the manual labor currently utilized in mushroom industry for harvesting. The system was built using commercially available off-the-shelf components with simple design for construction. Images of the mushrooms were acquired from two cameras to compute three dimensional physical attributes. The overhead (first) image was processed by software routines to isolate and identify the approximate centers ([x, y] coordinates) of individual mushrooms. This was followed by an edge tracing routine to obtain diameters of the mushroom heads. The inclined (second) camera was used in conjunction with structured lighting to extract the [x, z] coordinates in order to obtain the heights of the mushroom. Cameras had to be calibrated to predict the geometrical coordinates from the image coordinates. Several calibration techniques were reviewed, and a Direct Linear Transformation calibration routine was adopted for this work. Two calibration fixtures were utilized in the calibration. Error patterns were modeled to allow reduction of prediction errors. The overhead camera prediction errors were reduced from a maximum of 11 pixels to 2.15 pixels. The inclined camera prediction errors along the X and Z directions were independently considered for error reduction. The X direction errors varied as a cubic function with maximum being ±4.0 pixels. This error was reduced to ±1.40 pixels after applying the models. The Z direction errors were also reduced from 1.93 pixels to 0.66 pixels by developing error models.
Library of Congress Subject Headings
Mushrooms -- Selection -- Automation
Mushrooms -- Harvesting -- Automation
Image processing -- Digital techniques
South Dakota State University
Srinivasan, Jagadish, "A Machine Vision System and Calibration Procedure for Imaging Mushrooms for Harvest" (2000). Electronic Theses and Dissertations. 5942.