Pair-wise discrimination based on a stroke importance measure

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The pair-wise discriminator is a binary classifier that verifies the outcome of the recognizer if it belongs to a class in a pre-defined confusion pair database. It is difficult to discriminate a pair of characters that are very similar in shape except for a small difference, because the small difference can be overridden by the writing variation. This paper proposes a pair-wise discrimination method that discriminates similar characters by focusing on the structural difference between the two characters. It discriminates a pair of characters by comparing their matching scores between the input character and the models of the two characters, When the stroke matching scores are combined to compute the overall matching score, each stroke is assigned a weight to reflect its importance in discriminating the character pair. By assigning large weights to the discriminative strokes, the difference between the characters is emphasized. The stroke weights are systematically obtained by a neural network training algorithm. In the experiments, the recognition performance was significantly improved by applying the proposed method. (C) 2002 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Issue Date
2002-10
Language
English
Article Type
Article
Keywords

RECOGNITION; CHARACTERS

Citation

PATTERN RECOGNITION, v.35, no.10, pp.2259 - 2266

ISSN
0031-3203
URI
http://hdl.handle.net/10203/81841
Appears in Collection
CS-Journal Papers(저널논문)
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