Interactive Volume Exploration for Feature Detection and Quantification in Industrial CT Data

This paper presents a novel method for interactive exploration of industrial CT volumes such as cast metal parts, with the goal of interactively detecting, classifying, and quantifying features using a visualization-driven approach. The standard approach for defect detection builds on region growing, which requires manually tuning parameters such as target ranges for density and size, variance, as well as the specification of seed points. If the results are not satisfactory, region growing must be performed again with different parameters. In contrast, our method allows interactive exploration of the parameter space, completely separated from region growing in an unattended pre-processing stage. The pre-computed feature volume tracks a feature size curve for each voxel over time, which is identified with the main region growing parameter such as variance. A novel 3D transfer function domain over (density, feature size, time) allows for interactive exploration of feature classes. Featur...

• Type: Conference
• Year: 2008
• Where: VIS
• Authors: Markus Hadwiger, Laura Fritz, Christof Rezk-Salama, Thomas Höllt, Georg Geier, Thomas Pabel
• Keywords: Feature Size Curve, Feature Size Curves, IEEE Visualization, Region Growing Parameter, VIS 2008, Visualization