Isosurface extraction in the visualization toolkit using the Extrema Skeleton algorithm
Abstract (Summary)
Generating isosurfaces is a very useful technique in data visualization for
understanding the distribution of scalar data. Often, when the size of the data set is really
large, as in the case with data produced by medical imaging applications, engineering
simulations or geographic information systems applications, the use of traditional
methods like marching cubes makes repeated generation of isosurfaces a very time
consuming task. This thesis investigated the use of the Extrema Skeleton algorithm to
speed up repeated isosurface generation in the visualization package, Visualization
Toolkit (VTK). The objective was to reduce the number of non-isosurface cells visited to
generate isosurfaces, and to compare the Extrema Skeleton method with the Marching
Cubes method by monitoring parameters like time taken for the isosurfacing process and
number of cells visited. The results of this investigation showed that the Extrema
Skeleton method was faster for most of the datasets tested. For simple datasets with less
than 10% isosurface cells and complex datasets with less than 5% isosurface cells, the
Extrema Skeleton method was found to be significantly faster than the Marching Cubes
method. The time gained by the Extrema Skeleton method for datasets with greater than
15% isosurface cells was found to be insignificant. Based on the results of this study,
implementing the Extrema Skeleton method for the VTK software is a change worth
making because typical VTK users deal with datasets for which the Extrema Skeleton
method is significantly faster and also with datasets for which it is marginally faster than
the Marching Cubes method.
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Bibliographical Information:
Advisor:
School:The University of Tennessee at Chattanooga
School Location:USA - Tennessee
Source Type:Master's Thesis
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