Highly accurate recognition of printed Korean characters through an improved two-stage classification method

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摘要

This paper presents a recognition system which obtains a recognition rate higher than 99% for the printed Korean characters of multifont and multisize. We recognize a given input by first identifying the character type of the input and then recognizing its constituent graphemes. In order to improve the performance we incorporated three new ideas in our system: the expansion of the subimage areas used by the grapheme classifiers, an algorithm to accurately segment the horizontal vowel’s subimage areas, and a validation process to evaluate the result of the type classifier. Through experiments we confirmed that our system performs well in a multi-font and multi-size environment and that those three ideas actually contributed to improve the performance significantly.

论文关键词:Korean characters,OCR,Neural networks,Multi-font/multi-size,Grapheme recognition,Character type

论文评审过程:Received 13 May 1996, Revised 11 September 1997, Available online 7 June 2001.

论文官网地址:https://doi.org/10.1016/S0031-3203(97)00126-X