Masters Theses
Distance function applications of object comparison in artificial vision systems
Abstract
"In this work, we focus on the use of metrics on hyperspaces of two-dimensional continua to enrich the understanding of sight by modeling more of the vision process mathematically. Specifically, we address the topic of object comparison. How can a vision system distinguish between a coffee table and a basketball? Scientists disagree on the answer to this question. In this study, we focus on methods for object comparison using distance functions that work independently of the usual coordinate systems because the intended application is a biologically based robotic vision system, and coordinate-based computations are too slow and unwieldy to accurately model actual biological vision systems"--Abstract, page iii.
Advisor(s)
Insall, Matt
Committee Member(s)
Numbere, Tonye
Gadbury, Gary L.
Department(s)
Mathematics and Statistics
Degree Name
M.S. in Applied Mathematics
Publisher
University of Missouri--Rolla
Publication Date
Spring 2006
Pagination
viii, 106 pages
Rights
© 2006 Christina Michelle Ayres, All rights reserved.
Document Type
Thesis - Citation
File Type
text
Language
English
Subject Headings
Artificial vision
Hausdorff measures
Object-oriented programming (Computer science)
Optical pattern recognition
Thesis Number
T 8951
Print OCLC #
82367840
Link to Catalog Record
Full-text not available: Request this publication directly from Missouri S&T Library or contact your local library.
http://merlin.lib.umsystem.edu/record=b5771779~S5Recommended Citation
Ayres, Christina Michelle, "Distance function applications of object comparison in artificial vision systems" (2006). Masters Theses. 3856.
https://scholarsmine.mst.edu/masters_theses/3856
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