• DocumentCode
    2147070
  • Title

    Discovering Legible Chinese Typefaces for Reading Digital Documents

  • Author

    Zhang, Bing ; Li, Ying ; Suen, Ching Y. ; Zhang, Xuemin

  • Author_Institution
    Comput. Sci. & Software Eng. Dept., Concordia Univ., Montreal, QC, Canada
  • fYear
    2011
  • fDate
    18-21 Sept. 2011
  • Firstpage
    962
  • Lastpage
    966
  • Abstract
    More and more fonts have sprung up in recent years in digital publishing industry and reading devices. In this paper, we focus on methods of evaluating digital Chinese fonts and their typeface characteristics to seek a good way to enhance the character recognition rate. To accomplish this, we combined psychological analysis methods with statistical analysis. It involved an extensive survey of distinctive features of eighteen popular digital typefaces. Survey results were tabulated and analyzed statistically. Then another objective experiment was conducted using the best six fonts derived from the survey results. These experimental results reveal an effective way of choosing legible digital fonts most suitable for comfortable reading of books, magazines, newspapers, and for display of texts on cell-phones, e-books, and digital libraries, and finding out the features for improving character legibility of different Chinese typefaces. The relationships among legibility, eye-strain, and myopia, will be discussed.
  • Keywords
    character recognition; character sets; electronic publishing; natural language processing; psychology; statistical analysis; text analysis; visual perception; character legibility; character recognition rate; comfortable reading; digital Chinese fonts; digital documents reading; digital publishing industry; digital typefaces; eye-strain; legible Chinese typefaces; legible digital fonts; myopia; psychological analysis methods; reading devices; statistical analysis; text display; typeface characteristics; Accuracy; Character recognition; Educational institutions; Electronic publishing; Periodic structures; Statistical analysis; Text analysis; Chinese fonts; Digital Documents; Information display; Legibility; Typeface characteristics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis and Recognition (ICDAR), 2011 International Conference on
  • Conference_Location
    Beijing
  • ISSN
    1520-5363
  • Print_ISBN
    978-1-4577-1350-7
  • Electronic_ISBN
    1520-5363
  • Type

    conf

  • DOI
    10.1109/ICDAR.2011.195
  • Filename
    6065453