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Skeleton-Based Recognition of Chinese Calligraphic Character Image

Identifieur interne : 000B93 ( Main/Merge ); précédent : 000B92; suivant : 000B94

Skeleton-Based Recognition of Chinese Calligraphic Character Image

Auteurs : Kai Yu [République populaire de Chine] ; Jiangqin Wu [République populaire de Chine] ; Yueting Zhuang [République populaire de Chine]

Source :

RBID : ISTEX:B9FD00DFD1A4EC13D7E133C8A2D7ACE655BDF252

Abstract

Abstract: The large amount of digitized Chinese calligraphic works in existence is a valuable part of the Chinese cultural heritage. But they can hardly be recognized by optical character recognition (OCR) which performs well on machine printed characters against clean background, because there are so different styles of shape complexity characters. So the approaches of automatic Chinese calligraphic character recognition become more and more important. A novel skeletonization algorithm called MFITS (morphology-fused index table skeletonization) is proposed and a skeleton-based Chinese calligraphic character recognition method is proposed too. The experiments show that MFITS can extract skeletons with only a few deformations and the skeleton-based Chinese calligraphic character image recognition method has a good performance.

Url:
DOI: 10.1007/978-3-540-89796-5_24

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ISTEX:B9FD00DFD1A4EC13D7E133C8A2D7ACE655BDF252

Le document en format XML

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<div type="abstract" xml:lang="en">Abstract: The large amount of digitized Chinese calligraphic works in existence is a valuable part of the Chinese cultural heritage. But they can hardly be recognized by optical character recognition (OCR) which performs well on machine printed characters against clean background, because there are so different styles of shape complexity characters. So the approaches of automatic Chinese calligraphic character recognition become more and more important. A novel skeletonization algorithm called MFITS (morphology-fused index table skeletonization) is proposed and a skeleton-based Chinese calligraphic character recognition method is proposed too. The experiments show that MFITS can extract skeletons with only a few deformations and the skeleton-based Chinese calligraphic character image recognition method has a good performance.</div>
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