• DocumentCode
    510218
  • Title

    2D Line Matching Using Geometric and Intensity Data

  • Author

    Dong-Min Woo ; Dong-Chul Park ; Seung-Soo Han ; Beack, Seunghwa

  • Author_Institution
    Dept. of Inf. Eng., Myongji Univ., Gyeonggido, South Korea
  • Volume
    3
  • fYear
    2009
  • fDate
    7-8 Nov. 2009
  • Firstpage
    99
  • Lastpage
    103
  • Abstract
    We present a stereo matching method of 2D line segments for the detection of 3D line segment. Stereo line matching is a difficult task, since it relies on incomplete 2D line data. The proposed matching method is based on geometric and intensity information of 2D line segment. A set of line attributes is used to match a pair of 2D lines. Line attributes consist of intensity information and geometric information including length, orientation, and endpoint position. Multi-threshold technique has been employed in the implementation of the proposed method so that flexible and efficient matching capability can be attained. Aerial and satellite images are used for the experiments of the proposed method. The experimental results indicate that the proposed method generates accurate 3D line segments from aerial and satellite images.
  • Keywords
    computational geometry; image matching; object detection; stereo image processing; 2D line matching; 2D line segment; 3D line segment; geometric data; geometric information; intensity information; lines endpoint position; lines length; lines orientation; multithreshold technique; stereo matching method; Artificial intelligence; Computational intelligence; Computer vision; Data engineering; Image edge detection; Image processing; Image segmentation; Object recognition; Satellites; Stereo vision; 2D line; 3D line; geometric information; intensity information; stereo matching;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-3835-8
  • Electronic_ISBN
    978-0-7695-3816-7
  • Type

    conf

  • DOI
    10.1109/AICI.2009.287
  • Filename
    5376543