• Title/Summary/Keyword: Hangul Fonts

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The Effect of Hangul Font on Reading Speed in the Computer Environment

  • Kim, Sunkyoung;Lee, Ko Eun;Lee, Hye-Won
    • Journal of the Ergonomics Society of Korea
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    • v.32 no.5
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    • pp.449-457
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    • 2013
  • Objective: The aim of this study is to investigate the effect of Hangul font on reading speed when texts are displayed on the computer screen. Background: Reading performance is influenced by fonts. However, there are few studies of Hangul font from a cognitive perspective. Fonts could affect reading performance directly and indirectly, interacting with other visual-perceptual factors such as size, word spacing, and line spacing. Method: In experiment 1, two variables were manipulated; a frame condition(square frame non-square frame) and a stroke condition(serif sans-serif). According to each condition, one of the four fonts was applied to the texts. The height of the four fonts was controlled. The participants were asked to read aloud the presented texts. In experiment 2, the non-square frame fonts were adjusted to have approximately the same size, width, letter spacing, and word spacing as the square frame fonts. The experimental design and task used in experiment 2 were identical with experiment 1. Results: In general, reading speed was faster in the square frame fonts than in the non-square frame fonts. The reading speed was not significantly different across stroke conditions. Conclusion: The frame of Hangul font significantly influenced reading speed. These results suggest that the type of Hangul font is a factor to affect reading performance. Application: The frame of fonts should be considered in designing of new fonts. The square frame fonts should be the preferred choice to enhance legibility.

Design of Phoneme Fonts using an Analized Information of Hangul Syllable Forms (한글 음절의 유형 분석 정보에 의한 낱자 폰트의 설계)

  • 이계영;김규식;이상범
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.29B no.9
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    • pp.17-26
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    • 1992
  • This paper proposed an analysis method of common form for phonemes which is able to construct a Hangul syllable and designed the Choseong, Jungseong, and Jongseong phoneme fonts based on analized information. Also, It presents the algorithm which is able to construct the output of all Hangul syllables using 473 phoneme fonts. Through the experiment, an analized information and output algorithm could be applied to the design of Hangul fonts, effectively.

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A Study on Diversification of Hangul font classification system in digital environment (디지털 환경에서 한글 글꼴 분류체계 다양화 연구)

  • 이현주;홍윤미;손은미
    • Archives of design research
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    • v.16 no.1
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    • pp.5-14
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    • 2003
  • As the digital technology has improved, the numbers of Hangul font users have increased and their individual needs and taste are diversified. Therefore new and various Hangul fonts out of traditional form are developed and used. But under the present font classification system, it is hard to compare and analyze these various fonts. And the present classification system is hard to be the font user's guide for proper use of various Hangul fonts. For the better use of Hangul font, to diversify the font classification system is needed. So we propose the development of these thru classification standards. First, structural classification based on the structural character of Hangul. Second, image classification based on the visual images of each font. And third, usage classification based on the fonts proper usage in various media. For the development of various typographically balanced fonts and for the suitable and effective use of the various font, we must try to build the font classification system based on the diversified classification standards and build Hangul font database based on this classification system. Through these studies, we can expect the development of good quality fonts and the better use of these fonts.

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Shape Property Study of Hangul Font for Font Classification (글꼴 분류를 위한 한글 글꼴의 모양 특성 연구)

  • Kim, Hyun-Young;Lim, Soon-Bum
    • Journal of Korea Multimedia Society
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    • v.20 no.9
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    • pp.1584-1595
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    • 2017
  • Each cultural community has developed a variety of fonts to express their own language and characters. Hangul has also diversified its font shapes through changing the composition ratio and look of the consonants and vowels. Rather, thanks to the variety of these fonts, a considerable amount of time and effort must be devoted to the selection of a specific font shape. This is related to the fact that the current Hangul service and classification system process the font only with its name or the name of the manufacturer. It means that there is no consensus about the font shape classification system for Hangul. In this study, we propose a shape property set that can be a basis for classifying Hangul fonts. The font shape property set was generated by performing statistical analysis with features which have been studied by the font design experts and was verified through questionnaire using representative fonts based on the classification scheme defined by the Hangul font design classification system standard. This study is meaningful in that it is a study on shape classification properties of K-means and PCA statistical techniques based on font data rather than design field study.

Automatic Extraction of Hangul Stroke Element Using Faster R-CNN for Font Similarity (글꼴 유사도 판단을 위한 Faster R-CNN 기반 한글 글꼴 획 요소 자동 추출)

  • Jeon, Ja-Yeon;Park, Dong-Yeon;Lim, Seo-Young;Ji, Yeong-Seo;Lim, Soon-Bum
    • Journal of Korea Multimedia Society
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    • v.23 no.8
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    • pp.953-964
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    • 2020
  • Ever since media contents took over the world, the importance of typography has increased, and the influence of fonts has be n recognized. Nevertheless, the current Hangul font system is very poor and is provided passively, so it is practically impossible to understand and utilize all the shape characteristics of more than six thousand Hangul fonts. In this paper, the characteristics of Hangul font shapes were selected based on the Hangul structure of similar fonts. The stroke element detection training was performed by fine tuning Faster R-CNN Inception v2, one of the deep learning object detection models. We also propose a system that automatically extracts the stroke element characteristics from characters by introducing an automatic extraction algorithm. In comparison to the previous research which showed poor accuracy while using SVM(Support Vector Machine) and Sliding Window Algorithm, the proposed system in this paper has shown the result of 10 % accuracy to properly detect and extract stroke elements from various fonts. In conclusion, if the stroke element characteristics based on the Hangul structural information extracted through the system are used for similar classification, problems such as copyright will be solved in an era when typography's competitiveness becomes stronger, and an automated process will be provided to users for more convenience.

Intermediate Font Generation based on Shape Analysis of Hangul Glyph (한글 글립의 조형적 분석에 기반한 중간 폰트 생성)

  • Koo, Sang-Ok;Jung, Soon-Ki
    • Journal of KIISE:Computer Systems and Theory
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    • v.36 no.4
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    • pp.311-325
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    • 2009
  • This paper presents a method for analyzing Hangul glyphs with their outline fonts and obtaining intermediate fonts with two different fonts. The glyphs are represented and analyzed hierarchically such as characters, components(letters) and strokes. With the analysis results, we obtain several intermediate glyphs by morphing two different glyphs of same character. For a natural glyph contour morphing, we employ the curve morphing algorithm by weighted mean of strings. In addition, we provide four operations for transformation of glyphs with different topology. As a result, it is illustrated that the proposed Hangul glyphs morphing scheme is useful for new font generation from any exist fonts or handwritings.

Mnimizing Duplicates for Hangul Fonts using Composite Glyph of TrueType (트루타입의 합성 글립을 이용한 한글폰트의 중복성 최소화 방법)

  • Kim, Eun-Hui;Jeong, Geun-Ho;Choe, Jae-Yeong
    • Journal of KIISE:Software and Applications
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    • v.26 no.10
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    • pp.1230-1236
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    • 1999
  • 한글 폰트는 서로 상반된 장단점을 가진 조합형 폰트와 완성형 폰트로 구분된다. 완성형 폰트는 조합형과 비교하여 우수한 품질을 가지지만 폰트 제작에 더 많은 시간과 노력을 요구한다. 특히 완성형 폰트는 폰트내의 중복된 자소들의 정보를 중복해서 저장하므로 폰트 저장에 필요한 공간이 더 많이 필요하다. 본 논문에서는 트루타입의 합성 글립(Composite Glyph)을 이용하여 이들 중복된 자소를 최소화한 완성형 폰트를 구성하였다. 실험 결과 생성된 완성형 트루타입 폰트는 기존 완성형 폰트와 유사한 고수준의 품질을 유지하면서, 샘체의 경우 기존 폰트의 57.6%, 명조체의 경우 73.0%의 저장공간을 절약할 수 있었다.Abstract Hangul fonts are classified into 2 categories, complete type and combination type which have their own strength and weakness. The complete type shows a high quality of fonts, while the combination type takes less time, efforts, and storage space to develop. Since the Hangul makes a syllable by combining consonants with vowels, the complete type has many duplicates and requires a large storage space to save them. We present a method that minimizes the duplicates of the complete type of the Hangul using the composite glyph of TrueType. New fonts had high quality and saved storage space, for example Sam saved 57.6% and Myungjo saved 73.0% compared to old.

Application and Analysis of Emotional Attributes using Crowdsourced Method for Hangul Font Recommendation System (한글 글꼴 추천시스템을 위한 크라우드 방식의 감성 속성 적용 및 분석)

  • Kim, Hyun-Young;Lim, Soon-Bum
    • Journal of Korea Multimedia Society
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    • v.20 no.4
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    • pp.704-712
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    • 2017
  • Various researches on content sensibility with the development of digital contents are under way. Emotional research on fonts is also underway in various fields. There is a requirement to use the content expressions in the same way as the content, and to use the font emotion and the textual sensibility of the text in harmony. But it is impossible to select a proper font emotion in Korea because each of more than 6,000 fonts has a certain emotion. In this paper, we analysed emotional classification attributes and constructed the Hangul font recommendation system. Also we verified the credibility and validity of the attributes themselves in order to apply to Korea Hangul fonts. After then, we tested whether general users can find a proper font in a commercial font set through this emotional recommendation system. As a result, when users want to express their emotions in sentences more visually, they can get a recommendation of a Hangul font having a desired emotion by utilizing font-based emotion attribute values collected through the crowdsourced method.

A Study on Influence of Stroke Element Properties to find Hangul Typeface Similarity (한글 글꼴 유사성 판단을 위한 획 요소 속성의 영향력 분석)

  • Park, Dong-Yeon;Jeon, Ja-Yeon;Lim, Seo-Young;Lim, Soon-Bum
    • Journal of Korea Multimedia Society
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    • v.23 no.12
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    • pp.1552-1564
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    • 2020
  • As various styles of fonts were used, there were problems such as output errors due to uninstalled fonts and difficulty in font recognition. To solve these problems, research on font recognition and recommendation were actively conducted. However, Hangul font research remains at the basic level. Therefore, in order to automate the comparison on Hangul font similarity in the future, we analyze the influence of each stroke element property. First, we select seven representative properties based on Hangul stroke shape elements. Second, we design a calculation model to compare similarity between fonts. Third, we analyze the effect of each stroke element through the cosine similarity between the user's evaluation and the results of the model. As a result, there was no significant difference in the individual effect of each representative property. Also, the more accurate similarity comparison was possible when many representative properties were used.

Analysis of Extraction Performance according to the Expanding of Applied Character in Hangul Stroke Element Extraction (한글 획요소 추출 학습에서 적용 글자의 확장에 따른 추출 성능 분석)

  • Jeon, Ja-Yeon;Lim, Soon-Bum
    • Journal of Korea Multimedia Society
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    • v.23 no.11
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    • pp.1361-1371
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    • 2020
  • Fonts have developed as a visual element, and their influence has rapidly increased around the world. Research on font automation is actively being conducted mainly in English because Hangul is a combination character and the structure is complicated. In the previous study to solve this problem, the stroke element of the character was automatically extracted by applying the object detection by component. However, the previous research was only for similarity, so it was tested on various print style fonts, but it has not been tested on other characters. In order to extract the stroke elements of all characters and fonts, we performed a performance analysis experiment according to the expansion character in the Hangul stroke element extraction training. The results were all high overall. In particular, in the font expansion type, the extraction success rate was high regardless of having done the training or not. In the character expansion type, the extraction success rate of trained characters was slightly higher than that of untrained characters. In conclusion, for the perfect Hangul stroke element extraction model, we will introduce Semi-Supervised Learning to increase the number of data and strengthen it.