• 제목/요약/키워드: Hangul,.

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유니코드 환경에서의 올바른 한글 정규화를 위한 수정 방안 (Correction for Hangul Normalization in Unicode)

  • 안대혁;박영배
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제34권2호
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    • pp.169-177
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    • 2007
  • 현재 유니코드에서 한글텍스트의 정규화 기법은 완성형 현대한글 음절과 옛한글을 표현하는 조합형 한글 그리고 호환 자모등과 같이 사용할 경우 원래의 글자와는 전혀 다른 글자의 조합을 만들어내는 문제점이 있다. 이러한 문제점은 호환 한글 자모 및 기호들의 잘못된 정규화 변환과 유니코드의 한글자모 조합 규칙에서 자모와 완성형 현대한글 음절을 다시 조합하여 한글음절로 사용 할 수 있게 허용한 때문이다. 이는 정규화 형식을 처음 작성할 당시 옛한글의 사용을 고려하지 않았거나, 한글에 대한 올바른 이해가 부족한 상태에서 작성 된데 따른 결과라 하겠다. 따라서 본 연구에서는 유니코드 환경에서의 한글 코드와 특히 최근 들어 Web을 비롯하여 XML과 IDN에서 필연적으로 사용하는 정규화에 따른 문제점을 파악하고 이들을 올바르게 처리하기 위한 정규화의 수정 방안과 조합형 한글의 조합 규칙에 대한 수정 방안을 제안한다.

Atypical Character Recognition Based on Mask R-CNN for Hangul Signboard

  • Lim, Sooyeon
    • International journal of advanced smart convergence
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    • 제8권3호
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    • pp.131-137
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    • 2019
  • This study proposes a method of learning and recognizing the characteristics that are the classification criteria of Hangul using Mask R-CNN, one of the deep learning techniques, to recognize and classify atypical Hangul characters. The atypical characters on the Hangul signboard have a lot of deformed and colorful shapes beyond the general characters. Therefore, in order to recognize the Hangul signboard character, it is necessary to learn a separate atypical Hangul character rather than the existing formulaic one. We selected the Hangul character '닭' as sample data and constructed 5,383 Hangul image data sets and used them for learning and verifying the deep learning model. The accuracy of the results of analyzing the performance of the learning model using the test set constructed to verify the reliability of the learning model was about 92.65% (the area detection rate). Therefore we confirmed that the proposed method is very useful for Hangul signboard character recognition, and we plan to extend it to various Hangul data.

유니코드의 한글 인코딩 표준안 (Hangul Encoding Standard based on Unicode)

  • 안대혁;박영배
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제34권12호
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    • pp.1083-1092
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    • 2007
  • 현재 유니코드에서 한글 텍스트의 인코딩 기법은 '완성형 현대한글 음절'과 주로 옛한글을 표현하는데 사용되는 '자모 조합형 한글'로 나뉘고 있다. 그러나 정규화 변환과 유니코드의 한글자모 조합 규정에서 자모와 완성형 현대한글 음절을 다시 조합하여 한글음절로 사용할 수 있게 허용했기 때문에, 구현하는 사람마다 각기 서로 다르게 한글 인코딩을 하고 있다. 이는 인코딩과 정규화 형식을 처음 작성할 당시 옛한글의 확장 사용을 고려하지 않았거나, 한글에 대한 올바른 이해가 부족한 상태에서 작성된 데 따른 결과라 하겠다. 결과적으로 한 개의 한글음절에 대한 여러 가지 표현 방법이 존재함으로써 한글 문자열의 검색, 비교, 정렬에 문제점이 발생한다. 따라서 본 연구에서는 현재 사용되고 있는 한글 인코딩 방법을 중심으로 정규화에 의한 부작용 등의 문제점을 분석하고, 이들을 올바르게 처리하기 위한 효율적인 단일 한글 인코딩 표준 방안을 제안한다.

Some Characteristics of Hanmal and Hangul from the viewpoint of Processing Hangul Information on Computers

  • Kim, Kyong-Sok
    • 대한음성학회:학술대회논문집
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    • 대한음성학회 1996년도 10월 학술대회지
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    • pp.456-463
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    • 1996
  • In this paper, we discussed three cases to see the effects of the characteristics of Hangul writing system. In applications such as computer Hangul shorthands for ordinary people and pushbuttons with Hangul characters engraved, we found that there is much advantage in using Hangul. In case of Hangul Transliteration, we discussed some problems which are related with the characteristics of Hangul writing system. Shorthands use 3-set keyboards in England, America, and Korea. We saw how ordinary people can do computer Hangul shorthands, whereas only experts can do computer shorthands in other countries. Specifically, the facts that 1) Hangul characters are grouped into syllables (syllabic blocks) and that 2) there is already a 3-set Hangul keyboard for ordinary people allow ordinary people to do computer Hangul shorthands without taking special training as with English shorthands. This study was done by the author under the codename of 'Sejong 89'. In contrast like QWERTY or DVORAK, a 2-set Hangul keyboard cannot be used for shorthands. In case of English pushbuttons, one digit is associated with only one character. However, by engraving only syllable-initial characters on the phone pushbuttons, we can associate one Hangul "syllable" with one digit. Therefore, for a given number of digits, we can associate longer words or more meaningful words in Hangul than in English. We discussed the problems of the Hangul Transliteration system proposed by South Korea and suggested their solutions, if available. 1) We are incorrectly using the framework of transcription for transliteration. To solve the problem, the author suggests that a) we include all complex characters in the transliteration table, and that b) we specify syllable-initial and -final characters separately in the table. 2) The proposed system cannot represent independent characters and incomplete syllables. 3) The proposed system cannot distinguish between syllable-initial and -final characters.

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대용량 한글 텍스트 검색 엔진 HMG의 구현 (Implementation of Very Large Hangul Text Retrieval Engine HMG)

  • 박미란;나연묵
    • 한국멀티미디어학회논문지
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    • 제1권2호
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    • pp.162-172
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    • 1998
  • 본 논문에서는 영문 텍스트 검색 엔진인 MG(Managing Gigabytes) 시스템과 한글 형태소 분석기 HAM (Hangul Analysis Module)을 이용하여 기가바이트 크기의 텍스트 데이타 처리가 가능한 한글 텍스트 검색 엔진 HMG(Hangul MG)를 구현하였다. 한글 처리를 위해 KSC 5601 완성형 코드를 사용하여 데이타베이스 구축 단계와 질의 처리 단계에서 사용하였다. HMG의 개발을 위해 MG 시스템의 렉시칼 분석기와 파서, 인텍스 구성 모률을 수정하였다. HMG 시스템의 유용성을 보이기 위해 웹에서 한글 소설을 검색할 수 있도록 하는 N NOD (Novel On Demand) 시스템올 구현하였다. HMG 시스템은 한글이 포함된 대규모 전문 검색 시스템의 구축에 활용될 수 있다.

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이중언어능력의 조선족 아동과 청소년의 한글, 한자, 한글.한자혼합문 형태의 덩이글 이해에 관한 연구 (A Study on the Comprehension of Texts with Korean Hangul, Chinese Hanja and Hangul.Hanja among Korean-Chinese children and adolescents)

  • 윤혜경;박혜원;권오식
    • 아동학회지
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    • 제30권2호
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    • pp.15-28
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    • 2009
  • This study focused on the comprehension of texts written either in Korean script (Hangul) or Chinese script (Hanja). For this purpose, we measured the reading time and the correct response in text comprehension tasks with 104 Korean-Chinese children who were either 10 or 19 years old. There was a main effect of script : The reading time of Hanja texts was shorter than that of Hangul or Hangul Hanja mixed texts. But the older subjects who spent the same reading time in both Hangul and Hanja texts showed the longer reading time in Hangul Hanja mixed texts revealing the interaction between age and script. The correct response rate on the comprehension task was the highest in Hangul text. The results were discussed in relation to the independent dual language processing systems in Korean-Chinese.

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한글의 조합 규칙 표현 방법에 관한 연구 (An Effective Representation of Combination Rule for the Hangul Typeface Design)

  • 이병국;박윤범;이완규
    • 한국정보처리학회논문지
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    • 제3권6호
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    • pp.1580-1587
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    • 1996
  • 조합형 설계의 한글 폰트 디자인은 한글의 모아쓰기 원리를 이용하여 일관된 모 양을 유지하면서, 조합 가능한 활자체를 빠른 시간에 구성할 수 있는 장점이 있다. 그러나 균형감 있는 훌륭한 활자체를 개발하기 위해서는 설계할 자소의 수는 많아지 고 조합 방법은 복잡해진다. 본 논문에서는 조합형 설계의 성공적인 결과를 위하여 효율적인 조합 규칙 표현 방법을 제안한다.

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실물 이동 전화를 이용한 한글 입력 방식의 수행도 및 선호도 평가 (Evaluation for Performance and Preference of Hangul Eentry Methods using Real Mobile Phones)

  • 기도형
    • 대한인간공학회지
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    • 제25권3호
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    • pp.33-41
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    • 2006
  • This study empirically evaluated performance and preference of Hangul entry methods of five mobile phones through questionnaire and experiments. The questionnaire study revealed that 67% of respondents have been using SMS(short message service) more than six times a day, and that Hangul entry method is the most inconvenient thing when inputting Hangul characters. An experiment was conducted for assessing five Hangul entry methods in view of performance of entry time and errors, and subjective measures of satisfaction and preference. The results showed that Hangul entry method significantly affect objective performances as well as subjective measures at α=0.05 or 0.01. This study, in which real mobile phones were used, presented contrary result in terms of Hangul entry time, compared to the existing studies based on the conceptual models of Fitts' law or Hick-Hyman law.

HANDWRITTEN HANGUL RECOGNITION MODEL USING MULTI-LABEL CLASSIFICATION

  • HANA CHOI
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제27권2호
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    • pp.135-145
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    • 2023
  • Recently, as deep learning technology has developed, various deep learning technologies have been introduced in handwritten recognition, greatly contributing to performance improvement. The recognition accuracy of handwritten Hangeul recognition has also improved significantly, but prior research has focused on recognizing 520 Hangul characters or 2,350 Hangul characters using SERI95 data or PE92 data. In the past, most of the expressions were possible with 2,350 Hangul characters, but as globalization progresses and information and communication technology develops, there are many cases where various foreign words need to be expressed in Hangul. In this paper, we propose a model that recognizes and combines the consonants, medial vowels, and final consonants of a Korean syllable using a multi-label classification model, and achieves a high recognition accuracy of 98.38% as a result of learning with the public data of Korean handwritten characters, PE92. In addition, this model learned only 2,350 Hangul characters, but can recognize the characters which is not included in the 2,350 Hangul characters

딥러닝 학습을 이용한 한글 글꼴 자동 제작 시스템에서 글자 쌍의 매핑 기준 평가 (Evaluation of Criteria for Mapping Characters Using an Automated Hangul Font Generation System based on Deep Learning)

  • 전자연;지영서;박동연;임순범
    • 한국멀티미디어학회논문지
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    • 제23권7호
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    • pp.850-861
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    • 2020
  • Hangul is a language that is composed of initial, medial, and final syllables. It has 11,172 characters. For this reason, the current method of designing all the characters by hand is very expensive and time-consuming. In order to solve the problem, this paper proposes an automatic Hangul font generation system and evaluates the standards for mapping Hangul characters to produce an effective automated Hangul font generation system. The system was implemented using character generation engine based on deep learning CycleGAN. In order to evaluate the criteria when mapping characters in pairs, each criterion was designed based on Hangul structure and character shape, and the quality of the generated characters was evaluated. As a result of the evaluation, the standards designed based on the Hangul structure did not affect the quality of the automated Hangul font generation system. On the other hand, when tried with similar characters, the standards made based on the shape of Hangul characters produced better quality characters than when tried with less similar characters. As a result, it is better to generate automated Hangul font by designing a learning method based on mapping characters in pairs that have similar character shapes.