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Recognition of ambiguous pairs of totally unconstrained handwritten numerals

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Recognition of ambiguous pairs of totally unconstrained handwritten numerals

Tan, Yu (2002) Recognition of ambiguous pairs of totally unconstrained handwritten numerals. Masters thesis, Concordia University.

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Abstract

In order to improve the recognition rate of totally unconstrained handwritten numerals, a verification stage is added after classification to distinguish the ambiguous numerals between two or more classes. Two recognition methods, structural method and statistical method, are used to overcome the limitations of a single method and deliver a much more reliable recognition system. The recognition rate is 71.32% using structural method without verification. The verification stage improves the recognition rate from 71.32% to 87.50%. After combining the structural method with statistical method, the final recognition rate reached up to 95.59%

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Computer Science and Software Engineering
Item Type:Thesis (Masters)
Authors:Tan, Yu
Pagination:xii, 67 leaves : ill. ; 29 cm.
Institution:Concordia University
Degree Name:M. Comp. Sc.
Program:Computer Science and Software Engineering
Date:2002
Thesis Supervisor(s):Suen, Ching Y
Identification Number:QA 76 M26+ 2002 no.35
ID Code:1584
Deposited By: Concordia University Library
Deposited On:27 Aug 2009 17:20
Last Modified:13 Jul 2020 19:49
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