Robust Surface Detection for Variance Comparison and Dimensional Measurement

Christoph Heinzl, Roman Klingesberger, Johann Kastner, Meister Eduard Gröller
Robust Surface Detection for Variance Comparison and Dimensional Measurement
In Proceedings of Eurographics / IEEE VGTC Symposium on Visualization, pages 75-82. 2006.
[paper]

Information

Abstract

This paper describes a robust method for creating surface models from volume datasets with distorted density values due to artefacts and noise. Application scenario for the presented work is variance comparison and dimensional measurement of homogeneous industrial components in industrial high resolution 3D computed tomography (3D-CT). We propose a pipeline which uses common 3D image processing filters for pre-processing and segmentation of 3D-CT datasets in order to create the surface model. In particular, a pre-filtering step reduces noise and artefacts without blurring edges in the dataset. A watershed filter is applied on the gradient information of the smoothed data to create a binary dataset. Finally the surface model is constructed, using constrained elastic-surface nets to generate a smooth but feature preserving mesh of a binary volume. The major contribution of this paper is the development of the specific processing pipeline for homogeneous industrial components to handle large resolution data of industrial CT scanners. The pipeline is crucial for the following visual inspection of deviations.

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BibTeX

@inproceedings{heinzl_2006_RSDVCDM,
  title =      "Robust Surface Detection for Variance Comparison and
               Dimensional Measurement",
  author =     "Christoph Heinzl and Roman Klingesberger and Johann Kastner
               and Meister Eduard Gr{"o}ller",
  year =       "2006",
  abstract =   "This paper describes a robust method for creating surface
               models from volume datasets with distorted density values
               due to artefacts and noise. Application scenario for the
               presented work is variance comparison and dimensional
               measurement of homogeneous industrial components in
               industrial high resolution 3D computed tomography (3D-CT).
               We propose a pipeline which uses common 3D image processing
               filters for pre-processing and segmentation of 3D-CT
               datasets in order to create the surface model. In
               particular, a pre-filtering step reduces noise and artefacts
               without blurring edges in the dataset. A watershed filter is
               applied on the gradient information of the smoothed data to
               create a binary dataset. Finally the surface model is
               constructed, using constrained elastic-surface nets to
               generate a smooth but feature preserving mesh of a binary
               volume. The major contribution of this paper is the
               development of the specific processing pipeline for
               homogeneous industrial components to handle large resolution
               data of industrial CT scanners. The pipeline is crucial for
               the following visual inspection of deviations.",
  booktitle =  "Proceedings of Eurographics / IEEE VGTC Symposium on
               Visualization",
  publisher =  "IEEE CS",
  pages =      "75--82",
  keywords =   "Applications",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2006/heinzl_2006_RSDVCDM/",
}