Detection Model of Hangul Stroke Elements: Expansion of Non-Structured Font and Influence Evaluation by Stroke Element Combinations
With the increase of various media, fonts continue to be newly developed. In Korea, numerous ‘Hangul’ fonts are also being developed, and as a result, the need for research on determining the similarity between fonts is emerging. For example, when creating a document, the font to be used must be dow...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/12/2/383 |
| _version_ | 1797443460618256384 |
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| author | Soon-Bum Lim Jongwoo Lee Xiaotong Zhao Yoojeong Song |
| author_facet | Soon-Bum Lim Jongwoo Lee Xiaotong Zhao Yoojeong Song |
| author_sort | Soon-Bum Lim |
| collection | DOAJ |
| description | With the increase of various media, fonts continue to be newly developed. In Korea, numerous ‘Hangul’ fonts are also being developed, and as a result, the need for research on determining the similarity between fonts is emerging. For example, when creating a document, the font to be used must be downloaded from each computing environment. However, this is a very cumbersome process. If there is a font that is not supported in the system, the above problem can be easily solved by recommending the most similar font that can replace it. According to this need, we conducted various prior studies for similar font recommendations. As a result, we developed a ‘stroke element’ that exists in each consonant and vowel in Korean font and developed a font recommendation model using a stroke element. However, there is a limitation in that the existing research was studied only for the structured fonts corresponding to the printed type. Additionally, the font size was not considered in the font recommendation. In this study, two experiments were conducted to expand the font recommendation model by supplementing the limitations of existing studies. First, in order to enable similar font recommendations based on the stroke element even in fonts with various shapes, the font was classified according to the shape, and the stroke elements in each classification were detected. Second, when the font sizes were different, the change in the font recommendations result based on the stroke element was analyzed. In conclusion, we found that it was necessary to find a plan to extract stroke elements for font recommendation of fonts that do not belong to standard fonts. In addition, since the influence of the stroke element varies depending on the size of the font, we propose a stroke element weight model that can be used for recommendation by reflecting it. |
| first_indexed | 2024-03-09T12:57:22Z |
| format | Article |
| id | doaj.art-ea13e1cbbb42412db440bd0213f7296c |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-09T12:57:22Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-ea13e1cbbb42412db440bd0213f7296c2023-11-30T21:59:42ZengMDPI AGElectronics2079-92922023-01-0112238310.3390/electronics12020383Detection Model of Hangul Stroke Elements: Expansion of Non-Structured Font and Influence Evaluation by Stroke Element CombinationsSoon-Bum Lim0Jongwoo Lee1Xiaotong Zhao2Yoojeong Song3Department of IT Engineering, Research Institute of ICT Convergence, Sookmyung Women’s University, Cheongpa-ro 47-gil 100, Yongsan-gu, Seoul 04310, Republic of KoreaDepartment of IT Engineering, Research Institute of ICT Convergence, Sookmyung Women’s University, Cheongpa-ro 47-gil 100, Yongsan-gu, Seoul 04310, Republic of KoreaSchool of Digital Arts, Dalian Neusoft University of Information, Dalian 116023, ChinaSchool of Computer Science, Semyung University, Jecheon 27136, Republic of KoreaWith the increase of various media, fonts continue to be newly developed. In Korea, numerous ‘Hangul’ fonts are also being developed, and as a result, the need for research on determining the similarity between fonts is emerging. For example, when creating a document, the font to be used must be downloaded from each computing environment. However, this is a very cumbersome process. If there is a font that is not supported in the system, the above problem can be easily solved by recommending the most similar font that can replace it. According to this need, we conducted various prior studies for similar font recommendations. As a result, we developed a ‘stroke element’ that exists in each consonant and vowel in Korean font and developed a font recommendation model using a stroke element. However, there is a limitation in that the existing research was studied only for the structured fonts corresponding to the printed type. Additionally, the font size was not considered in the font recommendation. In this study, two experiments were conducted to expand the font recommendation model by supplementing the limitations of existing studies. First, in order to enable similar font recommendations based on the stroke element even in fonts with various shapes, the font was classified according to the shape, and the stroke elements in each classification were detected. Second, when the font sizes were different, the change in the font recommendations result based on the stroke element was analyzed. In conclusion, we found that it was necessary to find a plan to extract stroke elements for font recommendation of fonts that do not belong to standard fonts. In addition, since the influence of the stroke element varies depending on the size of the font, we propose a stroke element weight model that can be used for recommendation by reflecting it.https://www.mdpi.com/2079-9292/12/2/383Hangul stroke elementfont similarity evaluationweight calculation modelfont recommendation |
| spellingShingle | Soon-Bum Lim Jongwoo Lee Xiaotong Zhao Yoojeong Song Detection Model of Hangul Stroke Elements: Expansion of Non-Structured Font and Influence Evaluation by Stroke Element Combinations Electronics Hangul stroke element font similarity evaluation weight calculation model font recommendation |
| title | Detection Model of Hangul Stroke Elements: Expansion of Non-Structured Font and Influence Evaluation by Stroke Element Combinations |
| title_full | Detection Model of Hangul Stroke Elements: Expansion of Non-Structured Font and Influence Evaluation by Stroke Element Combinations |
| title_fullStr | Detection Model of Hangul Stroke Elements: Expansion of Non-Structured Font and Influence Evaluation by Stroke Element Combinations |
| title_full_unstemmed | Detection Model of Hangul Stroke Elements: Expansion of Non-Structured Font and Influence Evaluation by Stroke Element Combinations |
| title_short | Detection Model of Hangul Stroke Elements: Expansion of Non-Structured Font and Influence Evaluation by Stroke Element Combinations |
| title_sort | detection model of hangul stroke elements expansion of non structured font and influence evaluation by stroke element combinations |
| topic | Hangul stroke element font similarity evaluation weight calculation model font recommendation |
| url | https://www.mdpi.com/2079-9292/12/2/383 |
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