• DocumentCode
    495783
  • Title

    Recognition of Bridge over Water in High-Resolution Remote Sensing Images

  • Author

    Fu, Yili ; Xing, Kun ; Huang, Yongjie ; Xiao, Yongfei

  • Author_Institution
    Adv. Manuf. Technol. Center, Harbin Inst. of Technol., Harbin, China
  • Volume
    2
  • fYear
    2009
  • fDate
    March 31 2009-April 2 2009
  • Firstpage
    621
  • Lastpage
    625
  • Abstract
    Bridge is an important artificial target in the field of remote sensing analysis. A method for automatic recognition of bridges over water in high-resolution remote sensing images is presented. Firstly, we establish bridge knowledge models. Based on top-down knowledge-driven, the flow is composed of two steps: hypothesis and testing. Hypothesis is rough positioning including such techniques: waters segmentation, ROI extraction with morphology operator and connectivity sign, candidate regions detection. In testing process, the possible bridge is authenticated using gray features, and the parameters such as coordinates and azimuth of bridge can be obtained. Experiments are executed on the high-resolution remote sensing images, and the results confirm the validity of the proposed method.
  • Keywords
    bridges (structures); feature extraction; geophysical signal processing; image colour analysis; image recognition; image resolution; image segmentation; object recognition; terrain mapping; ROI extraction; automatic recognition; bridge recognition; gray features; high-resolution remote sensing images; morphology operator; rough positioning; testing process; water segmentation; Bridges; Flowcharts; Image recognition; Image segmentation; Morphology; Remote sensing; Rivers; Satellites; Strips; Testing; Knowledge-driven; Morphology; Recognition of bridge; Remote sensing image;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Engineering, 2009 WRI World Congress on
  • Conference_Location
    Los Angeles, CA
  • Print_ISBN
    978-0-7695-3507-4
  • Type

    conf

  • DOI
    10.1109/CSIE.2009.2
  • Filename
    5171413