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Title:Intelligent Vision System for the Detection of Protozoa on Microscope Slides
Author(s):O'Brien, John G., III
Doctoral Committee Chair(s):Reid, John F.
Department / Program:Mechanical Science and Engineering
Discipline:Mechanical Science and Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Engineering, Environmental
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.
Issue Date:2002
Description:306 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2002.
Other Identifier(s):(MiAaPQ)AAI3070035
Date Available in IDEALS:2015-09-25
Date Deposited:2002

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