Date of Award

12-1993

Document Type

Thesis

Degree Name

Master of Science

Department

Department of Electrical and Computer Engineering

First Advisor

Steven K. Rogers, PhD

Abstract

A machine which can read unconstrained words remains an unsolved problem. For example, automatic entry o handwritten documents into a computer is yet to be accomplished. Most systems attempt to segment letters o a word and read words one character at a time. Segmenting a handwritten word is very difficult and often, the confidence of the results is low. Another method which avoids segmentation altogether is to treat each word as a whole. This research investigates the use of Fourier Transform coefficients, computed from the whole word, for the recognition of handwritten words. To test this concept, the particular pattern recognition problem studied consisted of classifying four handwritten words. Buffalo, Vegas, Washington, City. Several feature subsets of the Fourier coefficients are examined. The best recognition performance of 76.2 was achieved when the Karhunen-Loeve transform was computed on the Fourier coefficients.

AFIT Designator

AFIT-GEO-ENG-93D-04

DTIC Accession Number

ADA274050

Comments

The author's Vita page is omitted.

Download

Share

COinS