Masters Theses

Abstract

“In today’s high tech world, information abounds in great volume. Thus finding a specific instance of something in a large collection of information requires the use of a search engine. There are many such search engines available for performing textual searches. However, there are few search engines available for graphics. Given the difficulty of searching for graphics in large volumes of data, this research has the objective of providing a new approach for conducting graphical searches that is not manually intensive. Unlike textual searches, graphical searches are more complex and present several problems including: different types of graphics, different file formats, determination of how to perform comparisons, and choosing attributes to compare. To address these problems, this thesis deals with two-dimensional vector graphics based on straight lines, describes a specific file format, uses a modified entity approach for performing comparisons, and determines a list of attributes. In developing the modified entity approach, a knowledge structure is defined to represent attributes and information particular to a 2D graphical object; such as: line length, number of lines, and number of nodes. The knowledge structure will be used in performing graphical comparisons and can be stored in a file for later retrieval. Also, developed are a set of algorithms that include: a learning algorithm for learning attributes from graphical objects, a comparison algorithm for performing the graphical comparison and a ranking algorithm for sorting search results based on a set of user defined criteria. After presenting the design of the modified entity approach, a discussion of the software system developed to implement the design will follow. Once completed, the software system is used to perform an experiment for the purpose of validating the correctness and usefulness of the 2D graphical search engine. Using a set of test graphics, both the experimental test cases and the results are presented”--Abstract, page iii.

Advisor(s)

St. Clair, Daniel C.

Committee Member(s)

Sabharwal, Chaman
Hahn, James H.

Department(s)

Computer Science

Degree Name

M.S. in Computer Science

Publisher

University of Missouri--Rolla

Publication Date

Fall 2000

Pagination

viii, 72 pages

Note about bibliography

Includes bibliographical references (pages 70-71).

Rights

© 2000 Michael Alton Fisher, All rights reserved.

Document Type

Thesis - Restricted Access

File Type

text

Language

English

Thesis Number

T 7863

Print OCLC #

45903501

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