Automatic Segmentation Techniques of Profile Measurement for Circle-Line Splining

Christoph-Peter Hinterleitner

Research output: ThesisDiploma Thesis

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This thesis addresses techniques for automatic registration and segmentation of 2D geometry measurement data associated with profiled steel tubing. The CAD model consists of a concatenation of many circular arcs and straight line segments, which form the closed profile. The registration and segmentation of the measurement data is a prerequisite to performing a least square fitting of the coupled geometric objects. Prior to fitting the segments of data are associated with specific geometric objects. The cross-section of the geometric objects is measured by a set of light-sectioning sensing heads arranged around the profile. In order to derive quantitative information from the measured data, the data points have to be registered and segmented prior to fitting. In the present work, techniques addressing the following tasks are presented: (1) template matching; (2) data segment assignment; (3) data sorting and (4) determination of transition points between the particular segments. Thereby, CAD data representing the ideal geometry is incorporated. The above process yield segmented and sorted data, ready for least square fitting. All methods are tested and verified with real measurement data, recorded from a automatic measuring system using five light-sectioning heads to capture the cross-section.
Translated title of the contributionAutomatische Segmentierung von 2D Messdaten in Kreis- und Liniensplining
Original languageEnglish
  • O'Leary, Paul, Supervisor (internal)
Award date25 Jun 2010
Publication statusPublished - 2010

Bibliographical note

embargoed until null


  • fitting line circle least squares matrix computation

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