Surface detection with subvoxel accuracy using 3D Gaussian facet model

Kai Wang, Dinghua Zhang, Jing Liu, Shunli Zhang, Xinbo Zhao

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

This paper presents a 3D edge detection algorithm based on Gaussian facet model. First we generalize the classic Haralick facet model and introduce the 3D Gaussian facet model using the Gaussian weighted least squares fitting, which uses spatial weights to express the relative importance of image samples in estimating model parameters. Then we employ the 3D integrated directional derivative gradient (IDDG) operator to robustly estimate the gradient direction, and along this direction the zeros of the second directional derivatives are computed to locate the subvoxel positions of the surface points. Experimental results show our method can effectively reduce the interference of adjacent edge and can achieve good performance in extracting edge points of small structures.

Original languageEnglish
Pages (from-to)1100-1106
Number of pages7
JournalJisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics
Volume19
Issue number9
StatePublished - Sep 2007

Keywords

  • Gaussian facet model
  • Industrial computer tomography
  • Moment
  • Subvoxel accuracy
  • Surface detection

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