Presidential Scholars Theses (1990 – 2006)

Awards/Availabilty

Open Access Presidential Scholars Thesis

First Advisor

Sarah Rebecca Thomas

Abstract

Computer vision and human vision are quite different. While a person can look at an object and easily recognize it, a computer is does not understand the the objects it is seeing. Finding axes and circles in an image is an intermediate step in designing a machine with the ability to recognize shapes and objects. Through the utilization of contour and smoothed local symmetry information, the main axes of an image are determined and may be used to facilitate shape and object analysis. A Hough transform algorithm detects the most popular lines from a set of candidate axis points. This conversion process also detects the optimal circles in an image. Through the use of Hough transform algorithms, these axes and circles are designated as being the best suited for the computer to recognize what it is seeing. These extensions bridge part of a gap between a collection of outlines and symmetric points to shape and eventual object recognition.

Date of Award

1995

Department

Department of Computer Science

Presidential Scholar Designation

A paper submitted in partial fulfillment of the requirements for the designation Presidential Scholar

Comments

If you are the rightful copyright holder of this Presidential Scholars thesis and wish to have it removed from the Open Access Collection, please submit an email request to scholarworks@uni.edu. Include your name and clearly identify the thesis by full title and author as shown on the work.

Date Original

1995

Object Description

1 PDF file (36 pages)

Date Digital

2-22-2018

Copyright

©1995 - Karissa E. Hobert

Type

document

Language

EN

File Format

application_pdf

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