• DocumentCode
    949014
  • Title

    Three-Dimensional Surface Mesh Segmentation Using Curvedness-Based Region Growing Approach

  • Author

    Jagannathan, Anupama ; Miller, Eric L.

  • Author_Institution
    Motorola Inc., Anaheim
  • Volume
    29
  • Issue
    12
  • fYear
    2007
  • Firstpage
    2195
  • Lastpage
    2204
  • Abstract
    A new parameter-free graph-morphology-based segmentation algorithm is proposed to address the problem of partitioning a 3D triangular mesh into disjoint submeshes that correspond to the physical parts of the underlying object. Curvedness, which is a rotation and translation invariant shape descriptor, is computed at every vertex in the input triangulation. Iterative graph dilation and morphological filtering of the outlier curvedness values result in multiple disjoint maximally connected submeshes such that each submesh contains a set of vertices with similar curvedness values, and vertices in disjoint submeshes have significantly different curvedness values. Experimental evaluations using the triangulations of a number of complex objects demonstrate the robustness and the efficiency of the proposed algorithm and the results prove that it compares well with a number of state-of-the-art mesh segmentation algorithms.
  • Keywords
    curve fitting; filtering theory; graph theory; image segmentation; iterative methods; mesh generation; solid modelling; surface fitting; curvedness-based region growing approach; iterative graph dilation; morphological filtering; outlier curvedness value; parameter-free graph-morphology; three-dimensional surface mesh segmentation; curvedness; graph morphology; mesh segmentation; shape descriptor; Algorithms; Artificial Intelligence; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/TPAMI.2007.1125
  • Filename
    4359293