Award Date

1-1-1995

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Computer Science

Number of Pages

115

Abstract

In this thesis we review existing algorithms for measuring shape similarity between polygons. We present a new approach to measure similarity based on the notion of annular profile. We also present the implementation of three shape measuring algorithms: signature function, turning function, and annular profile. The implementation is done by using the Visual C++ programming language. Finally, we discuss the comparative performances of the above three methods for capturing shape similarity. Measurement of shape similarity has applications in pattern recognition and artificial intelligence.

Keywords

Polygonal; Shapes; Similarity

Controlled Subject

Computer science; Artificial intelligence

File Format

pdf

File Size

3420.16 KB

Degree Grantor

University of Nevada, Las Vegas

Language

English

Permissions

If you are the rightful copyright holder of this dissertation or thesis and wish to have the full text removed from Digital Scholarship@UNLV, please submit a request to digitalscholarship@unlv.edu and include clear identification of the work, preferably with URL.

Rights

IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/

Download


COinS