Improving Visibility and Reducing Resistance of Writers to Fusion of Handwritten and Type Characters

  • Mikako SasakiEmail author
  • Junki Saito
  • Satoshi Nakamura
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11000)


Most Japanese people feel happy to receive a handwritten message, but they often have resistance to writing a message by hand. One of the reasons for this is that they are shy about showing their handwriting to others. In this study, we consider a technique that fuses handwriting with typeface in order to reduce the resistance to handwriting and improve the impression of the message. Experimental results demonstrate the visibility and readability of the considered fusion technique and show that the resistance to sending handwritten messages fused with typeface can be decreased.


Handwriting Type characters Fusion character 



This work was supported in part by JST, JST ACCEL Grant Number JPMJAC1602, Japan, and Meiji University Priority Research A.


  1. 1.
    Zebra Corporation: Attitude Survey on the Handwriting. Accessed 24 Mar 2018
  2. 2.
    The Agency for Cultural Affairs: The Public Opinion Poll on Japanese. Accessed 24 Mar 2018
  3. 3.
    Font Garage: What’s UD Font. Accessed 24 Mar 2018
  4. 4.
    Iwata Corporation: Iwata UD Font. Accessed 24 Mar 2018
  5. 5.
    Saito, J., Nakamura, S., Suzuki, M.: A method to increase reader’s empathy by merging their handwritten characters and text in speech balloon in digital comics. In: The Japanese Society for Artificial Intelligence, JSAI, Nagoya (2017). (in Japanese)Google Scholar
  6. 6.
    Zintnick, C.L.: Handwriting beautification using token means. In: ACM Special Interest Group on Computer Graphics and Interactive Techniques, vol. 32. SIGGRAPH, Anaheim (2013)Google Scholar
  7. 7.
    Zhu, X., Jin, L.: Calligraphic beautification of handwritten chinese characters: a patternized approach to handwriting transfiguration. Semant. Sch. (2008)Google Scholar
  8. 8.
    Kurihara, K., Goto, M., Ogata, J., Igarashi, T.: Speech pen: predictive handwriting based on ambient multimodal recognition. In: ACM SIGCHI Conference on Human Factors in Computing Systems, pp. 851–860. CHI, Montreal (2006)Google Scholar
  9. 9.
    Kambara, K., Tsukada, K., Onomatopen: painting using onomatopoeia. In: 9th International Conference on Entertainment Computing, pp. 43–54. ICEC, Seoul (2010)Google Scholar
  10. 10.
    Lin, J.-W., Hong, C.-Y., Chang, R.-I., Wang, Y.-C., Lin, S.-Y., Ho, J.-M.: Complete font generation of Chinese characters in personal handwriting style. In: 34th Computing and Communications Conference. IPCCC, Nanjing (2015)Google Scholar
  11. 11.
    Bernard, M., Liao, C.H., Mills, M.: The effects of font type and size on the legibility and reading time of online text by older adults. In: ACM SIGCHI Conference on Human Factors in Computing Systems, pp. 175–176. CHI, Seattle (2001)Google Scholar
  12. 12.
    Cai, D., Chi, C.-F., You, M.: The legibility threshold of Chinese characters in three-type styles. Int. J. Ind. Ergon. 27(1), 9–17 (2001)CrossRefGoogle Scholar
  13. 13.
    Liu, N., Ruifeng, Yu., Zhang, Y.: Effects of font size, stroke width, and character complexity on the legibility of Chinese characters. Hum. Fact. Ergon. Manuf. Serv. Ind. 26(3), 381–392 (2016)CrossRefGoogle Scholar
  14. 14.
    Morisawa: MORISAWA BIZ + . Accessed 24 Mar 2018
  15. 15.
  16. 16.
    Nakamura, S., Suzuki, M.M., Komatsu, T.: Average handwritten hiragana-characters are beautiful. Inf. Process. Soc. Jpn 57(12), 2599–2609 (2016). (in Japanese)Google Scholar
  17. 17.
    Mukai, S.: Analysis of common cognition of impression among japanese fonts and tea beverage packaging. In: 5th Kanesi Engineering and Emotion Research, pp. 1509–1519. KEER, Linköping (2014)Google Scholar
  18. 18.
    Mukai, S., Hibino, H., Koyama, S.: Differences in ratings of impressions between Japanese calligraphic styles and a Japanese font. Int. J. Affect. Eng. 16(2), 53–56 (2017)CrossRefGoogle Scholar
  19. 19.
    Henderson, P.W., Giese, J.L., Cote, J.A.: Impression management using typeface design. J. Mark. 68(4), 60–72 (2004)CrossRefGoogle Scholar
  20. 20.
    Miyoshi, M., Shimoshio, Y., Koga, H., Uchimura, K.: On evaluation of similarity between visual impressions of handwritten character using Kansei information. Inst. Image Inf. Telev. Eng. Proc. 24(51), 1–8 (2000). (in Japanese)Google Scholar
  21. 21.
    Inoue, M., Kobayashi, T.: The research domain and scale construction of adjective-pairs in a semantic differential method in Japan. Jpn. Assoc. Educ. Psychol. 33(3), 253–260 (1985). (in Japanese)CrossRefGoogle Scholar
  22. 22.
    Dalton, P., Maute, C., Oshida, A., Hikichi, S., Izumi, Y.: The use of semantic differential scaling to define the multidimensional representation of odors. J. Sens. Stud. 23(4), 485–497 (2008)CrossRefGoogle Scholar

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© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Meiji UniversityNakano-kuJapan

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