Award Date

1-1-2005

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Computer Science

First Committee Member

Evangelos Yfantis

Number of Pages

49

Abstract

This research mainly focuses on recognizing the handwritten characters on a form in order to automate the Medical Form processing. Several efficient algorithms have been developed by us so far, to separate the handwritten characters from printed text character; to separate the lines, words and each character. In this thesis, we concentrate on the recognition of the segmented handwritten characters. Different feature recognition algorithms are employed and their performance on a given training set is analyzed. We find a way to combine all these individual feature recognition algorithms by incorporating their interdependence. The reliability of these algorithms is determined in terms of Conditional Probabilities and a rule for classifying the input character based on the outputs of each individual feature recognition algorithms is identified from the observations.

Keywords

Character; Combining; Conditional; Handwritten; Multiple; Probabilities; Recognition; Recognizers

Controlled Subject

Computer science

File Format

pdf

File Size

1351.68 KB

Degree Grantor

University of Nevada, Las Vegas

Language

English

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