• myGriffith
    • Staff portal
    • Contact Us⌄
      • Future student enquiries 1800 677 728
      • Current student enquiries 1800 154 055
      • International enquiries +61 7 3735 6425
      • General enquiries 07 3735 7111
      • Online enquiries
      • Staff phonebook
    View Item 
    •   Home
    • Griffith Research Online
    • Conference outputs
    • View Item
    • Home
    • Griffith Research Online
    • Conference outputs
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

  • All of Griffith Research Online
    • Communities & Collections
    • Authors
    • By Issue Date
    • Titles
  • This Collection
    • Authors
    • By Issue Date
    • Titles
  • Statistics

  • Most Popular Items
  • Statistics by Country
  • Most Popular Authors
  • Support

  • Contact us
  • FAQs
  • Admin login

  • Login
  • Multi-font Script Identification Using Texture

    Author(s)
    Busch, Andrew
    Griffith University Author(s)
    Busch, Andrew W.
    Year published
    2006
    Metadata
    Show full item record
    Abstract
    The problem of determining the script and language of a document image has a number of important applications in the field of document analysis, for example as a precursor to OCR. Previous work has shown that visual texture is an effective method of performing script recognition, however such an approach is highly susceptible to changes in font. In this paper, a method of multi-font script recognition using a clustered discriminate function is proposed, allowing the training of a single model for each script class incorporating all fonts. Experimental evidence shows that such an approach can lead to significantly ...
    View more >
    The problem of determining the script and language of a document image has a number of important applications in the field of document analysis, for example as a precursor to OCR. Previous work has shown that visual texture is an effective method of performing script recognition, however such an approach is highly susceptible to changes in font. In this paper, a method of multi-font script recognition using a clustered discriminate function is proposed, allowing the training of a single model for each script class incorporating all fonts. Experimental evidence shows that such an approach can lead to significantly reduced error rates when classifying multi-font scripts.
    View less >
    Conference Title
    Proceedings of Microelectronic Research Conference 2005
    Publication URI
    http://hdl.handle.net/10072/13134
    Collection
    • Conference outputs

    Footer

    Disclaimer

    • Privacy policy
    • Copyright matters
    • CRICOS Provider - 00233E

    Tagline

    • Gold Coast
    • Logan
    • Brisbane - Queensland, Australia
    First Peoples of Australia
    • Aboriginal
    • Torres Strait Islander