• DocumentCode
    1556455
  • Title

    Geometric reasoning for recognition of three-dimensional object features

  • Author

    Marefat, M. ; Kashyap, R.L.

  • Author_Institution
    Sch. of Electr. Eng., Purdue Univ., W. Lafayette, IN, USA
  • Volume
    12
  • Issue
    10
  • fYear
    1990
  • fDate
    10/1/1990 12:00:00 AM
  • Firstpage
    949
  • Lastpage
    965
  • Abstract
    A method for extracting manufacturing shape features from the boundary representation of a polyhedral object is presented. In this approach, the depressions of the part are represented as cavity graphs, which are in turn used as a basis for hypothesis generation-elimination. The proposed cavity graphs are an extended representation in which the links reflect the concavity of the intersection between two faces, and the node labels reflect the relative orientation of the faces comprising the depression. Because previous methods have limited success in handling interactions, emphasis is put on automatic analysis of depressions which are formed by the interactions of primitive features. It is shown that although there is a unique subgraph for each primitive feature, every cavity graph does not correspond to a unique set of primitive features. Consequently, since the cavity graph of a depression may not be the union of the representations for the involved primitives, the concept of virtual links for the formal analysis of the depressions based on cavity graphs is introduced. Finally, a suitable method for automatic determination of the virtual links is presented. This method is based on combining topologic and geometric evidences, and uses a combination of Dempster-Shafer decision theory and clustering techniques to reach its conclusions. Experimental results are presented for a number of examples
  • Keywords
    decision theory; graph theory; pattern recognition; Dempster-Shafer decision theory; cavity graphs; clustering; feature extraction; geometric reasoning; hypothesis generation-elimination; manufacturing shape features; pattern recognition; polyhedral object; primitive features; three-dimensional object features; topologic evidence; Computational geometry; Computational intelligence; Computer aided manufacturing; Data mining; Decision theory; Design automation; Feature extraction; Manufacturing automation; Pattern recognition; Shape;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/34.58868
  • Filename
    58868