전자공학회논문지B (Journal of the Korean Institute of Telematics and Electronics B)
- 제32B권1호
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- Pages.147-153
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- 1995
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- 1016-135X(pISSN)
다층 퍼셉트론을 이용한 한글 필기체 온라인 인식
Hangul Handwritten Character On-Line Recognition using Multilayer Perceptron
초록
In this paper, we propose the position- and size-independent handwritten on-line Korean character recognition system using multilayer neural networks which are trained with error back-propagation learning algorithm and the features of Hanguel consonants and vowels. Starting point, end point, and three vectors from starting point to end point of each stroke of characters inputted from mouse or tablet are applied as inputs of neural networks. If double consonants and vowels are separated by single consonants and vowels, all consonants and vowels have at most four strokes. Therefore, four neural networks learn the consonants and the vowels having each number of strokes. Also, we propose the algorithm of separating the consonants and vowels and constructing a character.
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