Award Date

1-1-2005

Degree Type

Thesis

Degree Name

Master of Science (MS)

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

1.32 MB

Degree Grantor

University of Nevada, Las Vegas

Language

English

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