Masters Theses

Abstract

"In creating digital maps from paper maps, the paper map must first be scanned to produce a raster image, and then converted into vector format. Vector format allows non-graphical cartographic information to be stored along with the graphical objects. At the United States Geological Survey, the conversion from raster to vector format is performed by a commercial software package. The package also attempts to classify the graphical objects based on shape, line patterns, and other information gained from the raster file. Since the package frequently fails to classify a significant percentage of the elements in the map, manual map analysis and classification, a slow and costly process, is necessary.

The current project implements template matching in an effort to reduce the amount of manual analysis necessary for hydrography files (files containing all water data from a map). Lines appearing in a hydrography file are either solid (shoreline or perennial streams) or made up of the repeated pattern of a dash and three dots (intermittent streams). The Wise Intermittent Stream Recognition and Detection (WISRD) system has been created to identify lines having the intermittent stream pattern, thereby decreasing the amount of manual editing necessary for hydrography files.

The choice of template matching as a pattern recognition technique has proven to be quite beneficial in the classification process. The WISRD system succeeded in significantly reducing the number of unclassified lines upon its completion"--Abstract, page iii.

Advisor(s)

Wilkerson, Ralph W.
Erçal, Fikret

Committee Member(s)

Insall, Matt

Department(s)

Computer Science

Degree Name

M.S. in Computer Science

Comments

A report which is substantially this thesis is available here for download.

Publisher

University of Missouri--Rolla

Publication Date

Spring 1993

Pagination

vii, 49 pages

Note about bibliography

Includes bibliographical references (page 48).

Rights

© 1993 Angela G. Lammers, All rights reserved.

Document Type

Thesis - Restricted Access

File Type

text

Language

English

Thesis Number

T 6570

Print OCLC #

28767802

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