• DocumentCode
    1943250
  • Title

    Subsign detection with region-growing from contrasted seeds

  • Author

    Puthon, Anne-Sophie ; Moutarde, Fabien ; Nashashibi, Fawzi

  • Author_Institution
    Robot. Centre, Mines ParisTech, Paris, France
  • fYear
    2012
  • fDate
    16-19 Sept. 2012
  • Firstpage
    969
  • Lastpage
    974
  • Abstract
    Speed limit determination systems for cars based on vision are more and more developed. Roadsign detection is nowadays a well managed problem. However, in some situations this information is not sufficient to know the speed limitation. Restrictions are sometimes applicable and specified by subsigns. These small rectangles often provide essential information about the applicability scope (vehicle type, condition, lane, etc.) of speed limits. We present an approach of subsign localization based on region growing with an initial step of seed selection using morphological reconstruction. A comparison is also performed with three other techniques based on edge, color and graph on two databases gathering French and German subsigns. The obtained subsign correct detection is above 65%.
  • Keywords
    automobiles; graph theory; image colour analysis; object detection; traffic engineering computing; visual databases; French subsigns; German subsigns; applicability scope; cars; color techniques; edge techniques; graph techniques; morphological reconstruction; region growing; road sign detection; seed selection; speed limit determination systems; subsign detection; subsign localization; vehicle type; Databases; Image color analysis; Image edge detection; Image reconstruction; Intelligent vehicles; Roads; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Transportation Systems (ITSC), 2012 15th International IEEE Conference on
  • Conference_Location
    Anchorage, AK
  • ISSN
    2153-0009
  • Print_ISBN
    978-1-4673-3064-0
  • Electronic_ISBN
    2153-0009
  • Type

    conf

  • DOI
    10.1109/ITSC.2012.6338826
  • Filename
    6338826