• DocumentCode
    1723342
  • Title

    Entropy-Based Similarity Evaluation and Visualization of Cartographic Symbol Sets

  • Author

    Wang, Florence Ying ; Takatsuka, Masahiro

  • Author_Institution
    Sch. of IT, Univ. of Sydney, Sydney, NSW, Australia
  • fYear
    2015
  • Firstpage
    718
  • Lastpage
    725
  • Abstract
    In cartographic symbology, the evaluation of a symbol set´s visual similarity is an important and frequently required task. Usually, after a set of map symbols are designed, the visual similarity of symbols need to be manually examined. To fully automate this task, in this paper, we propose two approaches based on entropy calculated on SOM surface for quantifying and visualizing the visual similarities of cartographic symbol sets. Using our approaches, the visual similarities of multiple symbol sets can be compared efficiently. Apart from evaluating the visual similarities of cartographic symbol sets, both of our methods are also suitable for applications where comparing the visual similarities of multiple image datasets are required.
  • Keywords
    cartography; entropy; image matching; self-organising feature maps; SOM surface; cartographic symbol sets visualization; cartographic symbology; entropy-based similarity evaluation; multiple image datasets; multiple symbol sets; self-organizing maps; symbol visual similarity; Entropy; Equations; Feature extraction; Mathematical model; Shape; Vectors; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Applications of Computer Vision (WACV), 2015 IEEE Winter Conference on
  • Conference_Location
    Waikoloa, HI
  • Type

    conf

  • DOI
    10.1109/WACV.2015.101
  • Filename
    7045955