Range Image Feature Extraction with Varying Degrees of Data Irregularity

S Suganthan, SA Coleman, BW Scotney

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

15 Citations (Scopus)

Abstract

The use of range images has become prominent in the field of computer vision. Due to the irregular nature of range image data that occurs with a number of sensors, edge detection techniques for range images are often based on scan line data approximations and hence do not employ exact data locations. We present a finite element based approach to the development of gradient operators that can be applied to both regularly and irregularly distributed range images. We have created synthetic irregularly distributed range images for each edge type, and the gradient operators developed are evaluated with respect to their performance in edge detection across varying levels of data irregularity.
Original languageEnglish
Title of host publicationUnknown Host Publication
PublisherIEEE Computer Society
Pages33-40
Number of pages8
DOIs
Publication statusPublished (in print/issue) - Sept 2007
EventInternational Machine Vision and Image Processing Conference (IMVIP 2007) - Maynooth, Ireland
Duration: 1 Sept 2007 → …

Conference

ConferenceInternational Machine Vision and Image Processing Conference (IMVIP 2007)
Period1/09/07 → …

Keywords

  • edge detection
  • feature extraction
  • finite element analysis
  • gradient methods

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