A Study on Hanguel Character Recognition using GRNN

자소 인식 신경망을 이용한 한글 문자 인식에 관한 연구

  • 장석진 (한국전자통신연구소) ;
  • 강선미 (고려대학교 부설정보통신기술공동연구소) ;
  • 김혁구 (고려대학교 대학원 전자공학과) ;
  • 노우식 (고려대학교 대학원 전자공학과) ;
  • 김덕진 (고려대학교 대학원 전자공학과)
  • Published : 1994.01.01

Abstract

This paper describes the recognition of the printed Hanguel(Korean Character) using Neural Network. In this study, Neural network is used in only specific classification. Hanguel is classified globally by using template matching. Neural network is learned using the segmented grapheme. The grapheme of Hanguel is segmented using the structural method. Neural network is constructed, which is corresponded to the kind and the shape of graphemes. Each neural network is multi layer perceptron. The learning algorithm is the modified error back propagation using descending epsilon method. With five test character sets, the recognition rate of 94.95% is obtained.

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