Detection of surface creases in range data

  • Authors:
  • Alexander Belyaev;Elena Anoshkina

  • Affiliations:
  • Max-Planck-Institut für Informatik, Saarbrücken, Germany;Max-Planck-Institut für Informatik, Saarbrücken, Germany

  • Venue:
  • IMA'05 Proceedings of the 11th IMA international conference on Mathematics of Surfaces
  • Year:
  • 2005

Quantified Score

Hi-index 0.00

Visualization

Abstract

We propose a fully automatic and view-independent computational procedure for detecting salient curvature extrema in range data. Our method consists of two major steps: (1) smoothing given range data by applying a nonlinear diffusion of normals with automatic thresholding; (2) using a Canny-like non-maximum suppression and hysteresis thresholding operations for detecting crease pixels. A delicate analysis of curvature extrema properties allows us to make those Canny-like image processing operations orientation-independent. The detected patterns of creases can be considered as ‘shape fingerprints'. The proposed method can be potentially used for shape recognition, quality evaluation, and matching purposes.