• Journal of KIISE:Software and Applications
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• v.34 no.2
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• pp.169-177
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• 2007

Hangul text normalization in current Unicode makes wrong Hangul syllable problems when using with precomposed modern Hangul syllables and composing old Hangul by using conjoining-Hangul Jamo and compatibility Hangul Jamo. This problem comes from allowing incorrect normalization form of compatibility Hangul Jamo and Hangul Symbol and also permitting to use conjoining-Hangul Jamo mixture with precomposed Hangul syllable in Unicode Hangul composing rule. It is caused by lack of consideration of old Hangul and/or insufficient understanding of Hangul code processing when writing specification for normalization forms in Unicode. Therefore on this paper, we study Hangul code in Unicode environment, specifically problems of normalization used for Web and XML, IDN in nowadays. Also we propose modification of Hangul normalization methods and Hangul composing rules for correct processing of Hangul normalization in Unicode.

• International journal of advanced smart convergence
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• v.8 no.3
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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.

• Journal of KIISE:Software and Applications
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• v.34 no.12
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• pp.1083-1092
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• 2007

In Unicode, two types of Hangul encoding schemes are currently in use, namely, the "precomposed modern Hangul syllables" model and the "conjoining Hangul characters" model. The current Unicode Hangul conjoining rules allow a precomposed Hangul syllable to be a member of a syllable which includes conjoining Hangul characters; this has resulted in a number of different Hangul encoding implementations. This unfortunate problem stems from an incomplete understanding of the Hangul writing system when the normalization and encoding schemes were originally designed. In particular, the extended use of old Hangul was not taken into consideration. As a result, there are different ways to represent Hangul syllables, and this cause problem in the processing of Hangul text, for instance in searching, comparison and sorting functions. In this paper, we discuss the problems with the normalization of current Hangul encodings, and suggest a single efficient rule to correctly process the Hangul encoding in Unicode.

• Proceedings of the KSPS conference
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• 1996.10a
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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.

• Journal of Korea Multimedia Society
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• v.1 no.2
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• pp.162-172
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• 1998

In this paper, we implement a gigabyte Hangul text retrieval engine HMG(Hangul MG) which is based on the English text retrieval engine MG(Managing Gigabytes) and the Hangul lexical analyzer HAM(Hangul Analysis Module). To support Hangul information, we use the KSC 5601 code in the database construction and query processing stages. The lexical analyzer, parser, and index construction module of the MG system are modified to support Hangul information. To show the usefulness of HMG system, we implemented a NOD(Novel On Demand) system supporting the retrieval of Hangul novels on the WWW. The proposed system HMG can be utilized in the construction of massive full-text information retrieval systems supporting Hangul.

• Korean Journal of Child Studies
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• v.30 no.2
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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.

• The Transactions of the Korea Information Processing Society
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• v.3 no.6
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• pp.1580-1587
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• 1996

The Hangul font design by using Hangul automata is more economical than other system in terms of the time to generate whole Hangul font set. In order to obtain good quality of Hangul font by this system, it is known that more Hangul jamo font primitives rules. In this paper, we present an effective combing rules in order to generate Hangul font set and to provide an integrated capabilities in Hangul font design environment.

• Journal of the Ergonomics Society of Korea
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• v.25 no.3
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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.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.27 no.2
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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

• Journal of Korea Multimedia Society
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• v.23 no.7
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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.