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

• Published in: IEEE transactions on visualization and computer graphics Vol. 14; no. 6; pp. 1507 - 1514
• Main Authors: Hadwiger, M., Laura, F., Rezk-Salama, C., Hollt, T., Geier, G., Pabel, T.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01-11-2008; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Automotive engineering; Building materials; Classification; Computed tomography; Computer Graphics; Computer vision; Construction industry; Data visualization; Density; Equipment Failure Analysis - methods; Exploration; Imaging, Three-Dimensional - methods; Index Terms— Industry - instrumentation; Interactive; Manufacturing industries; Materials Testing - methods; Metals industry; Multi-Dimensional Transfer Functions; Non-Destructive Testing; Nondestructive testing; Pattern Recognition, Automated - methods; Region Growing; Specifications; Studies; Three dimensional; Tomography, X-Ray Computed - methods; Transfer functions; User-Computer Interface; Variance; Volume Rendering
• ISSN: 1077-2626; 1941-0506
• DOI: 10.1109/TVCG.2008.147

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. Features and feature size curves can also be explored individually, which helps with transfer function specification and allows coloring individual features and disabling features resulting from CT artifacts. Based on the classification obtained through exploration, the classified features can be quantified immediately.