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Fuzzy vector median-based surface smoothing.

Yuzhong Shen1, Kenneth E Barner

  • 1Department of Electrical and Computer Engineering, University of Delaware, Newark, DE 19716, USA. yshen@ece.udel.edu

IEEE Transactions on Visualization and Computer Graphics
|June 27, 2008
PubMed
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This study introduces a novel fuzzy vector median (FVM) filter for smoothing triangular mesh surfaces. The FVM filter effectively reduces noise while preserving surface details, offering an advantage over existing methods.

Area of Science:

  • Computer Graphics
  • Computational Geometry
  • Image Processing

Background:

  • Surface smoothing is crucial for applications involving 3D models.
  • Traditional median filters struggle with vector data and preserving fine details.
  • Fuzzy ordering theory offers enhanced noise reduction capabilities.

Purpose of the Study:

  • To introduce a novel fuzzy vector median (FVM) filter for triangular mesh surface smoothing.
  • To enhance noise reduction while preserving geometric features in 3D surfaces.
  • To provide an efficient and effective alternative to existing surface smoothing algorithms.

Main Methods:

  • A two-step approach involving surface normal smoothing via FVM filtering.
  • Integration of smoothed surface normals using least squares error (LSE) criteria for vertex updates.

Related Experiment Videos

  • Extension of fuzzy ordering theory to vector data for the development of the FVM filter.

    • Main Results:

    • The FVM filter demonstrates superior performance in surface normal smoothing compared to existing algorithms.
    • The combined FVM and LSE method effectively minimizes noise and preserves surface details.
    • Simulation results validate the proposed method's advantages over common surface smoothing techniques.

    Conclusions:

    • The proposed FVM-based surface smoothing method is effective and efficient.
    • The technique offers significant improvements in noise reduction and detail preservation for triangular meshes.
    • The method is simple to implement and computationally efficient.