• 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
  • Role of Resolution in Noisy Pattern Matching

    Author(s)
    James, Alex Pappachen
    Dimitrijev, Sima
    Griffith University Author(s)
    Dimitrijev, Sima
    James, Alex P.
    Year published
    2010
    Metadata
    Show full item record
    Abstract
    Natural variability and limited number of library instances influence the matching performance and robustness of automatic pattern analysis methods. A data representation method that utilizes the local structures from the original data with a focus to effectively use the full resolution of data vector is presented. Using plant and face database, the issue of resolution, limitations in the number of library instances, and variability were addressed. Interestingly, the method shows an automatic matching improvement of over 22% under noisy and difficult matching condition.Natural variability and limited number of library instances influence the matching performance and robustness of automatic pattern analysis methods. A data representation method that utilizes the local structures from the original data with a focus to effectively use the full resolution of data vector is presented. Using plant and face database, the issue of resolution, limitations in the number of library instances, and variability were addressed. Interestingly, the method shows an automatic matching improvement of over 22% under noisy and difficult matching condition.
    View less >
    Conference Title
    INFORMATION PROCESSING AND MANAGEMENT
    Volume
    70
    DOI
    https://doi.org/10.1007/978-3-642-12214-9_21
    Subject
    Signal Processing
    Publication URI
    http://hdl.handle.net/10072/35566
    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