Machine vision microscopy as an on-line sensor for bioprocesses
A machine vision microscopy system (combination of video hardware and software and microscope for automated identification) was developed for classifying and counting microscopic objects in a Bacillus thuringiensis (Bt) fermentation. Image morphology properties consisting of area, perimeter, major length, minor length, number of holes, area of holes, and perimeter of holes were collected for vegetative cells, spores and protein crystals, and cells with included spores and crystals. Spatial resolution was 0.1333 $\mu$m/pixel in the horizontal direction and 0.1667 $\mu$m/pixel in the vertical direction.
Biology, Microbiology, Engineering, Agricultural
University of Illinois - Urbana-Champaign
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University of Illinois at Urbana-Champaign