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A recognition algorithm for chinese characters in diverse fonts

Identifieur interne : 001A01 ( Main/Exploration ); précédent : 001A00; suivant : 001A02

A recognition algorithm for chinese characters in diverse fonts

Auteurs : XIANLI WU [République populaire de Chine] ; MIN WU [États-Unis]

Source :

RBID : Pascal:04-0074302

Descripteurs français

English descriptors

Abstract

This paper proposes an algorithm for recognizing Chinese characters in many diverse fonts including Song, Fang, Kai, Hei, Yuan, Lishu, Weibei, and Xingkai. The algorithm is based on features derived from Peripheral Direction Contributivity and utilizes a set of dictionaries. A 3-level matching is first performed with respect to each dictionary. The distance measures associated with these matchings are then fed into a central discriminator to output the final recognition result. We propose a new multi-dictionary matching algorithm for use in the central discriminator that utilizes estimated information of neighborhood fonts. Experiments have been performed on a practical OCR software system whose recognition kernel is based on the proposed algorithm. Fast and accurate recognition has been accomplished both in title recognition involving all of the 8 fonts and in main-body recognition that usually involves the first 4 most commonly used fonts.


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Le document en format XML

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<div type="abstract" xml:lang="en">This paper proposes an algorithm for recognizing Chinese characters in many diverse fonts including Song, Fang, Kai, Hei, Yuan, Lishu, Weibei, and Xingkai. The algorithm is based on features derived from Peripheral Direction Contributivity and utilizes a set of dictionaries. A 3-level matching is first performed with respect to each dictionary. The distance measures associated with these matchings are then fed into a central discriminator to output the final recognition result. We propose a new multi-dictionary matching algorithm for use in the central discriminator that utilizes estimated information of neighborhood fonts. Experiments have been performed on a practical OCR software system whose recognition kernel is based on the proposed algorithm. Fast and accurate recognition has been accomplished both in title recognition involving all of the 8 fonts and in main-body recognition that usually involves the first 4 most commonly used fonts.</div>
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