Recognition of handwritten Chinese characters via short line segments
Identifieur interne : 003206 ( Main/Exploration ); précédent : 003205; suivant : 003207Recognition of handwritten Chinese characters via short line segments
Auteurs : Hsi-Jian Lee [République populaire de Chine] ; Bin Chen [République populaire de Chine]Source :
- Pattern Recognition [ 0031-3203 ] ; 1991.
Abstract
A system to recognize handwritten Chinese characters is presented. In the first stage, short line segments are extracted, where a new efficient algorithm is proposed, based on accumulated chain codes, for line approximation. In the feature extraction stage, features of each character are computed, which are further defined by the features of its composing line segments. In the matching stage, dynamic programming is first used to calculate the similarity between a segment of the input character and a segment of the reference character, and then the similarity between the two characters is computed. In order to reduce the number of candidates, a coarse classification algorithm is proposed. The recognition rate for 150 characters is about 90%, excluding the error in coarse classification.
Url:
DOI: 10.1016/0031-3203(92)90052-K
Affiliations:
Links toward previous steps (curation, corpus...)
- to stream Istex, to step Corpus: 000623
- to stream Istex, to step Curation: 000615
- to stream Istex, to step Checkpoint: 002442
- to stream Main, to step Merge: 003387
- to stream Main, to step Curation: 003206
Le document en format XML
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<front><div type="abstract" xml:lang="en">A system to recognize handwritten Chinese characters is presented. In the first stage, short line segments are extracted, where a new efficient algorithm is proposed, based on accumulated chain codes, for line approximation. In the feature extraction stage, features of each character are computed, which are further defined by the features of its composing line segments. In the matching stage, dynamic programming is first used to calculate the similarity between a segment of the input character and a segment of the reference character, and then the similarity between the two characters is computed. In order to reduce the number of candidates, a coarse classification algorithm is proposed. The recognition rate for 150 characters is about 90%, excluding the error in coarse classification.</div>
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