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UBC Theses and Dissertations
Machine recognition of typewritten characters based on shape descriptors Kanciar, Eugene J.A.
Abstract
An optical character recognition technique for typewritten letters was developed with application to a personal reading machine for the blind. The feature extraction process defined a character in terms of lines and shapes which are closely related to a person's description of form. The system was developed to identify all upper and lower-case typewritten characters in the alphabet. A letter was described by any combination of seven basic features, usually in a 3 x 3 feature matrix. The extraction of topological (or structural) properties had several advantages; a very small feature dictionary with about 100 code-word entries; quick and simple training procedure for a new font; and, a strong capability to handle character deformities. A separate technique, based on edge examination, was developed to identify characters with prominent diagonal features. Sequential classification was employed throughout the entire system so that recognition was made once a sufficiently unique measure was satisfied. Tests on both repeated characters and typewritten passages produced approximately 97% accuracy when the system was applied to three fonts which varied from a stylized to a serifless print. For a scanning rate of 60 wpm, a recognition speed of two characters per second was achieved. The system was developed on a PDP-12 computer and is fully compatible for realization on a PDP-8 computer with 8K of memory.
Item Metadata
Title |
Machine recognition of typewritten characters based on shape descriptors
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Creator | |
Publisher |
University of British Columbia
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Date Issued |
1974
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Description |
An optical character recognition technique for typewritten letters was developed with application to a personal reading machine for the blind. The feature extraction process defined a character in terms of lines and shapes which are closely related to a person's description of form. The system was developed to identify all upper and lower-case typewritten characters in the alphabet. A letter was described by any combination of seven basic features, usually in a 3 x 3 feature matrix. The extraction of topological (or structural) properties had several advantages; a very small feature dictionary with about 100 code-word entries; quick and simple training procedure for a new font; and, a strong capability to handle character deformities. A separate technique, based on edge examination, was developed to identify characters with prominent diagonal features. Sequential classification was employed throughout the entire system so that recognition was made once a sufficiently unique measure was satisfied.
Tests on both repeated characters and typewritten passages produced approximately 97% accuracy when the system was applied to three fonts which varied from a stylized to a serifless print. For a scanning rate of 60 wpm, a recognition speed of two characters per second was achieved. The system was developed on a PDP-12 computer and is fully compatible for realization on a PDP-8 computer with 8K of memory.
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Genre | |
Type | |
Language |
eng
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Date Available |
2010-01-20
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Provider |
Vancouver : University of British Columbia Library
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Rights |
For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.
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DOI |
10.14288/1.0065610
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URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
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Campus | |
Scholarly Level |
Graduate
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Aggregated Source Repository |
DSpace
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Item Media
Item Citations and Data
Rights
For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.