Visualizing Industrial CT Volume Data for Nondestructive Testing Applications

  • Authors:
  • Runzhen Huang;Kwan-Liu Ma;Patrick McCormick;William Ward

  • Affiliations:
  • University of California at Davis;University of California at Davis;Los Alamos National Laboratory;Los Alamos National Laboratory

  • Venue:
  • Proceedings of the 14th IEEE Visualization 2003 (VIS'03)
  • Year:
  • 2003

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Abstract

This paper describes a set of techniques developed for the visualization of high-resolution volume data generated from industrial computed tomography for nondestructive testing (NDT)applications. Because the data are typically noisy and contain fine features, direct volume rendering methods do not always give us satisfactory results. We have coupled region growing techniques and a 2D histogram interface to facilitate volumetric feature extraction. The new interface allows the user to conveniently identify, separate or composite, and compare features in the data. To lower the cost of segmentation, we show how partial region growing results can suggest a reasonably good classification function for the rendering of the whole volume. The NDT applications that we work on demand visualization tasks including not only feature extraction and visual inspection, but also modeling and measurement of concealed structures in volumetric objects. An efficient filtering and modeling process for generating surface representation of extracted features is also introduced. Four CT data sets for preliminary NDT are used to demonstrate the effectiveness of the new visualization strategy that we have developed.