• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.10
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• pp.747-754
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• 1991

In this paper, we studies the on-line recognition of handwritten character using WLD(weighted levenshtein distance) algorithm with parallelism. The Hangeul can be separated for unit of phonemes and the alphanumeric can be separated for unit of characters. And, we studies the parallelism and the concurrency of the WLD algorithm for realization of special-purpose processor. By the simulation result for 10, 000 characters in practical sentences, the recognition rate of strokes in obtained 96.57$\%$ and the separation rate for phonemes and characteristics is obtained 95.4$\%$.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.9
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• pp.8-16
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• 1992

This paper presents a method which can recognized the Handwritten Korean characters by using a Context-Free Grammar. The input characters are thinned in order to dwindle the mount of data, the thinned characters are converted into one-dimension strings according to six-forms. when the point of contact among phonemes is found, two phonemes are seperated respectively by marking the index mark (\) at the points. The Context-Free Grammar to input characters is classified into group grammars concerning the similarity of phonemes, input characters are parsed by making use of the Pushdown automata method. As the bent parts in the Handwritten characters are found frequently, We try to correct the bent parts by using the parsing distance measure, which recognize characters according to minium value caused by measuring the weight distance between two sentences. In this experiment, the recognition rate shows 93.8% to 275 Handwritten Korean characters.

• Annual Conference on Human and Language Technology
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• 2000.10d
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• pp.63-67
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• 2000

In order to develop a character recognition system, it is an essential preceding work that gathers an image data of the standard. On this purpose a data of the digitized images of a handwritten characters was collected. The types of a gathered image data are Korean character, Chiness character, Numeral, English character, Special character, and so on. This paper deals with a handwritten character image data base, and the image data base different from the general storage structure of a lame capacity multimedia was designed and builded.

• Annual Conference on Human and Language Technology
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• 2015.10a
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• pp.194-197
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• 2015

Long Short-term Memory Network(LSTM) 기반 Recurrent Neural Network(RNN)는 순차 데이터를 모델링 할 수 있는 딥 러닝 모델이다. 기존 RNN의 그래디언트 소멸 문제(vanishing gradient problem)를 해결한 LSTM RNN은 멀리 떨어져 있는 이전의 입력 정보를 볼 수 있다는 장점이 있어 음성 인식 및 필기체 인식 등의 분야에서 좋은 성능을 보이고 있다. 또한 LSTM RNN 모델에 의존성(전이 확률)을 추가한 LSTM CRF모델이 자연어처리의 한 분야인 개체명 인식에서 우수한 성능을 보이고 있다. 본 논문에서는 한국어 문장의 지배소가 문장 후위에 나타나는 점에 착안하여 Backward 방식의 LSTM CRF 모델을 제안하고 이를 한국어 의미역 결정에 적용하여 기존 연구보다 더 높은 성능을 얻을 수 있음을 보인다.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.1
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• pp.114-119
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• 1986

In this paper, an algorithm for the on-line recognition of handwritten Hangeul is proposed. The strokes are recognized by the minimum distance parser. The phonemes are separated by the finite-state automata resulted from the state graph of phonemes which are produced by the order of strokes. By simulation result for 3,000 characteristics in practical sentences, the recognition rate of strokes is obtained to be 98.5% and the separation rate of phonemes is obtained to be 92.5%.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.5
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• pp.769-776
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• 1987

A method of on-line recognition of Korean characters (Hangeul) by augmented conterxt free grammar is described in this paper. Syntactic analysis with context free grammar oftern has ambiguity. Insufficient description of relations among Hangrul sub-patterns causes this ambiguity can be determined through repetition of experiments. Flexible syntactic analysis is executed by adapting the condition to the (advice)part of augmented context free grammar. The ratio of correct recognition of this method is more than 99%.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.1
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• pp.29-37
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• 1989

This paper presents an application of the extended DP matching method to the on-line recognition of cursive Hangeul (Korean characters). We decrease the number of matching's objects by performing rough classification matching which makes the best use of features in the first and the last segment of Hangeul. By adding the extraction function of the basic character patterns to DP matching method, we try to calculate precisely the difference among Hangeul. The extraction of the basic character patterns is done by examining the features of segments in character. Applying the extended DP matching method to the on-line recognition of cursive Hangeul, absorption of writing motion and stable separation of strokes can be performed with flexibility.

• Archives of design research
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• v.14
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• pp.321-333
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• 1996

The typeface of the Shhnch 'ongjon woodblocks is unsophisticated and old-fashioned while at the same time having a tidiness and strength that give it its special appeal. This is the typeface used in publishing novPls for sale to the common people during the latter half of the Choson Dynasty_ Their demands could not be satisfied with most currently available literature. which was intended to suit the tastes of the official class. As a result of a development to overcome the unbalanced use of space characteristic of letterforms that followed the geometric principles of early Hangul. the typeface followed the refined. feminine "hrushstroke" style of kungch 'e. establishing itself as a "rough" face displaying the characteristics of carved. woodblock printing in answer to the needs of the common p-eople who had the greatest need of Hangul during the time of its f1owering. The Shhnch 'ongjon face is characterized by thin horizontal strokes. thick vertical strokes. and the appearance of being condensed left to right. They possess simple yet varied form. With these characteristics the Shimch' ongjon typeface. if revived and compared to other typefaces. has a beauty of structure and composition and a unique. modern lmage with excellent readability. giving it great significance for modern r langul typography.r langul typography.

• Annual Conference on Human and Language Technology
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• 1995.10a
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• pp.131-136
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• 1995

최근들어 자연스럽게 필기된 한글을 인식함으로써 정보 입력 과정을 자동화하기 위한 오프라인 한글 글씨 인식에 관한 연구가 활발히 진행되고 있다. 오프라인 한글 글씨 인식에 관한 연구에 있어서 반드시 확보되어야 하는 연구 환경으로 대용량 오프라인 한글 글씨 데이타베이스의 구축을 들 수 있는데, 본 논문에서는 시스템공학연구소 국어공학센터의 국어 정보 베이스 개발사업의 일환으로 추진중인 오프라인 한글 글씨 데이타베이스의 구축현황에 대해 간략히 소개하고자 한다. 오프라인 한글 글씨 데이타베이스의 구축은 크게 글씨 데이타베이스 설계, 글씨 데이타 수집, 용지 스캔 및 문자 단위 분할, 데이타베이스 검증의 4 단계로 구성된다. 본 연구에서는 다양한 변형을 갖는 글씨체의 수집을 데이타베이스 구축시 가장 고려해야 할 요소로 삼았으며, 고품질의 일관성 있는 글씨 데이타베이스 구축을 위해 데이타베이스 설계 단계와 검증 단계에 많은 시간을 할애했다. 마지막으로 본 연구에서는 WWW(World Wide Web)의 HTML(Hyper Text Markup Language)을 이용하여 편리 한 사용자 인터페이스를 구현함으로써 사용자들이 쉽게 한글 글씨 영상을 검색 할 수 있음은 물론 인식 알고리즘의 개발에 사용 가능한 형태의 화일을 제공받을 수 있도록 구성하고 있다. 현재는 KS C 완성형 한글 2,350자 중에서 사용 빈도순 상위 520자에 대한 한글 글씨 1,000벌을 수집하여 명도영상 데이타베이스를 구축 중에 있으며, 향후 2년간 나머지 1,830자에 대한 한글 글씨 데이타를 수집하여 데이타베이스를 완성하고자 한다. 구축된 글씨 데이타베이스는 조만간 국내의 오프라인 한글 글씨 인식 연구자들에게 제공되어 우수한 인식 알고리즘의 개발을 위한 중요한 실험 데이타로서 사용될 예정이며, 개발된 인식 시스템에 대한 객관적인 성능 평가에 있어서도 크게 기여하여 국내의 오프라인 한글 글씨 인식에 관한 연구를 활성화시켜주는 계기가 될 것으로 기대된다.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.3
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• pp.132-140
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• 1994

SCRIPT (Symbol/Character Recognition In Pen-based Technology) is an algorithm for on-line recognition of handwriting Hangeul. English upperacase letters, decimal digits, and some keyboard symbols. The shape of handwriting symbols has a large variation even when written by the same person. Though the feature analysis approach using a conventional decision tree is efficient, it is not robust under shape variations and prone to misclassification. Thus, a new method to overcome this shortcoming is necessary. In this paper, a feature analysis algorithm using two fuzzy decision trees which utilize the hierarchical property of the pattern is proposed. The first tree is used to represent the stroke shape, and the other tree is used to represent the relation between the strokes. since this method stores various possibilities. it is robust to shape variations and can readily modify false selections. In addition, there is a large increase in the recognition rate of high-level patterns due to low-level candidated. Experimental results show 91% recognition rate for Hangeul at the recognition speed of 0.33 second per character, and the recognition rate of alphanumerics and some keyboard symbols is 95% at 0.08 second per symbol. This is 8~18% increase in the recognition rate over th method not applying fuzzy decision trees.