• DocumentCode
    2503554
  • Title

    The Snippet Statistics of Font Recognition

  • Author

    Lidke, Jakub ; Thurau, Christian ; Bauckhage, Christian

  • Author_Institution
    Fraunhofer IAIS, St. Augustin, Germany
  • fYear
    2010
  • fDate
    23-26 Aug. 2010
  • Firstpage
    1868
  • Lastpage
    1871
  • Abstract
    This paper considers the topic of automatic font recognition. The task is to recognize a specific font from a text snippet. Unlike previous contributions, we evaluate, how the frequencies of certain letters or words influence automatic recognition systems. The evaluation provides estimates on the general feasibility of font recognition under various changing conditions. Results on a data-set containing 747 different fonts shows that precision can vary between 16% and 94%, dependent on (i) which letters are provided, (ii) how many letters are provided, and (iii) which language is used - as these factors considerably influence the text snippet statistics. As a second contribution, we introduce a novel bag-of-features based approach to font recognition.
  • Keywords
    character sets; optical character recognition; statistical analysis; text analysis; automatic font recognition; automatic recognition systems; bag-of-features; text snippet statistics; Character recognition; Histograms; Image recognition; Pixel; Shape; Training; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2010 20th International Conference on
  • Conference_Location
    Istanbul
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4244-7542-1
  • Type

    conf

  • DOI
    10.1109/ICPR.2010.461
  • Filename
    5597228