• DocumentCode
    1747183
  • Title

    Visual recognition of planar panels with line features

  • Author

    Jeong, Mun Ho ; Kim, Jin-Oh ; Kweon, In So

  • Author_Institution
    Dept. of Mech. Eng., Osaka Univ., Japan
  • Volume
    1
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    184
  • Abstract
    The authors introduce a new method for visual recognition of panels with stiffeners for the sub-assembly process of ship-building. Recognition with existing CAD data is to find the location/orientation of stiffeners and panels, panel ID numbers and approximate welding lines in sequence. The method extracts line features from original images and uses five-line invariants for the recognition. The existing invariant approaches have been proved successful for planar object recognition, but the large search space with combinatorial explosion has been the main hurdle in real application. To reduce this search space, the authors propose a new method with line convex hull (LCH) and indexing logic filter (ILF). In addition, a hierarchical database is constructed to retrieve corresponding model features directly. They have performed experiments using fifteen different welding panels, and demonstrate the feasibility of their method for the recognition of planar objects
  • Keywords
    assembling; computer vision; construction industry; feature extraction; object recognition; ships; welding; CAD data; approximate welding lines; hierarchical database; indexing logic filter; line convex hull; line features; panel ID numbers; panel stiffeners; planar object recognition; planar panels; search space; ship-building; sub-assembly process; visual recognition; Data mining; Explosions; Feature extraction; Filters; Image recognition; Indexing; Logic; Object recognition; Spatial databases; Welding;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics, 2001. Proceedings. ISIE 2001. IEEE International Symposium on
  • Conference_Location
    Pusan
  • Print_ISBN
    0-7803-7090-2
  • Type

    conf

  • DOI
    10.1109/ISIE.2001.931779
  • Filename
    931779