Intelligent Vision System for the Detection of Protozoa on Microscope Slides
O'Brien, John G., III
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https://hdl.handle.net/2142/83777
Description
Title
Intelligent Vision System for the Detection of Protozoa on Microscope Slides
Author(s)
O'Brien, John G., III
Issue Date
2002
Doctoral Committee Chair(s)
Reid, John F.
Department of Study
Mechanical Science and Engineering
Discipline
Mechanical Science and Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Engineering, Environmental
Language
eng
Abstract
Three approaches were evaluated for suitability in the confirmation process. These methods were then checked for correspondence between the results indicated by an expert human observer. Most texture measurements alone were not found to be useful. A heuristic method, was computationally more efficient and performed with an 80 percent accuracy. Using a neural network classifier, performance ranged from 50 to 100 percent depending on the parameters tested. Overall, the correspondence between the system and expert suggested a strong relationship to classifications of unknown objects.
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