Distance function applications of object comparison in artificial vision systems

Author

Christina Michelle Ayres

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.

Recommended 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