• DocumentCode
    498294
  • Title

    New Method of Primitive Feature Recognition Based on Graphics Comparability

  • Author

    Liu, Jianping ; Ye, Bangyan ; Peng, Jianxi ; Wu, Bo

  • Author_Institution
    Foshan Polytech. Coll., Foshan, China
  • Volume
    3
  • fYear
    2009
  • fDate
    19-21 May 2009
  • Firstpage
    424
  • Lastpage
    428
  • Abstract
    For improving validity and efficiency of 3D reconstruction from 2D engineering drawings, this paper presents a new method of primitive feature recognition based on graphics comparability determining of view loop. Main steps of this method are as follows: Firstly separate three views of single or combined primitive bodies by loop search, and then code view loops of primitive body and calculate graphics similarity measure of two view loops, further determine type of primitive body by projection rules and extract different information of modeling feature for different primitive bodies. Based on the mentioned above, different reconstruction algorithms are applied for different primitive bodies. Application module of 3D intelligent reconstruction system is developed together with the tools of Object ARX 2008 and Visual C# 2.0 in AutoCAD 2008 environment and this algorithm is actualized. The validity of feature recognition is verified by examples.
  • Keywords
    CAD; computer graphics; image reconstruction; mechanical engineering computing; 2D engineering drawings; 3D intelligent reconstruction system; 3D reconstruction; AutoCAD 2008; Object ARX 2008; Visual C# 2.0; graphics comparability; primitive feature recognition; reconstruction algorithms; view loop determination; Computer graphics; Data mining; Educational institutions; Engineering drawings; Intelligent systems; Intelligent vehicles; Pattern matching; Reconstruction algorithms; Shape measurement; Solids;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems, 2009. GCIS '09. WRI Global Congress on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-0-7695-3571-5
  • Type

    conf

  • DOI
    10.1109/GCIS.2009.465
  • Filename
    5209129