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 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.