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Detection of surface creases in range data

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish
Title of host publicationMathematics of Surfaces XI
PublisherSpringer
Pages50-61
Number of pages12
ISBN (Electronic)9783540318354
ISBN (Print)9783540282259
DOIs
Publication statusPublished - 2005
Event11th IMA International Conference 2005 - Loughborough, United Kingdom
Duration: 5 Sept 20057 Sept 2005

Publication series

NameLecture Notes in Computer Science
Volume3604
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th IMA International Conference 2005
Country/TerritoryUnited Kingdom
CityLoughborough
Period5/09/057/09/05

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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