Curtin University Homepage
  • Library
  • Help
    • Admin

    espace - Curtin’s institutional repository

    JavaScript is disabled for your browser. Some features of this site may not work without it.
    View Item 
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item

    Semi-automated segment generation for geographic novelty detection using edge and area metrics

    Access Status
    Fulltext not available
    Authors
    Fourie, C.
    van Niekerk, A.
    Mucina, Ladislav
    Date
    2012
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Fourie, C. and van Niekerk, A. and Mucina, L. 2012. Semi-automated segment generation for geographic novelty detection using edge and area metrics. South African Journal of Geomatics. 1 (2): pp. 133-148.
    Source Title
    South African Journal of Geomatics
    Additional URLs
    http://www.ajol.info/index.php/sajg/article/viewFile/107006/96913
    ISSN
    2225-8531
    School
    Department of Environment and Agriculture
    URI
    http://hdl.handle.net/20.500.11937/6973
    Collection
    • Curtin Research Publications
    Abstract

    An approach to generating accurate image segments for land-cover mapping applications is to model the process as an optimisation problem. Area-based empirical discrepancy metrics are used to evaluate instances of generated segments in the search process. An edge metric, called the pixel correspondence metric (PCM), is evaluated in this approach as a fitness function for segmentation algorithm free-parameter tuning. The edge metric is able to converge to user-provided reference segments in an earth observation mapping problem when adequate training data are available. Two common metaheuristic search functions were tested, namely particle swarm optimisation (PSO) and differential evolution (DE). The edge metric is compared with an area-based metric, regarding classification results of the land-cover elements of interests for an arbitrary problem. The results show the potential of using edge metrics, as opposed to area metrics, for evaluating segments in an optimisation-based segmentation algorithm parameter-tuning approach.

    Related items

    Showing items related by title, author, creator and subject.

    • Seabed biotope characterisation based on acoustic sensing
      Kloser, Rudolf J (2007)
      The background to this thesis is Australia’s Oceans Policy, which aims to develop an integrated and ecosystem-based approach to planning and management. An important part of this approach is the identification of natural ...
    • Scaling species richness and endemism of tropical dry forests on oceanic islands
      Gillespie, T.; Keppel, Gunnar; Pau, S.; Price, J.; Jaffre, T.; O'Neill, K. (2013)
      Aim: We examine variation in woody plant species richness and endemism within tropical dry forest on oceanic islands and determine what climatic and biogeographic metrics best explain native species richness and endemism ...
    • DBCAMM: A novel density based clustering algorithm via using the Mahalanobis metric
      Ren, Yan; Xiaodong, Liu; Liu, Wan-Quan (2012)
      In this paper we propose a new density based clustering algorithm via using the Mahalanobis metric. This is motivated by the current state-of-the-art density clustering algorithm DBSCAN and some fuzzy clustering algorithms. ...
    Advanced search

    Browse

    Communities & CollectionsIssue DateAuthorTitleSubjectDocument TypeThis CollectionIssue DateAuthorTitleSubjectDocument Type

    My Account

    Admin

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Follow Curtin

    • 
    • 
    • 
    • 
    • 

    CRICOS Provider Code: 00301JABN: 99 143 842 569TEQSA: PRV12158

    Copyright | Disclaimer | Privacy statement | Accessibility

    Curtin would like to pay respect to the Aboriginal and Torres Strait Islander members of our community by acknowledging the traditional owners of the land on which the Perth campus is located, the Whadjuk people of the Nyungar Nation; and on our Kalgoorlie campus, the Wongutha people of the North-Eastern Goldfields.