Interactive data visualization is inherently an iterative trial-and-error process searching for an ideal set of parameters for classifying and rendering features of interest in the data. This paper presents 3-d region growing based techniques that can assist the users to locate and define features of interest in volume data more quickly and more accurately. One technique employs partial region growing to generate a 2-d transfer function that effectively reveals the full features of interest. The other technique uses the result of full region growing to systematically construct a boundary surface for the extracted features. The resulting polygonal representation of the boundary surface can facilitate comparison, measurement, and simulation. A visual assessment method is suggested by using the extracted volume and surface information. These techniques either shorten or completely eliminate the typical trial-and-error step in the process of interactive data exploration.

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 one 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 compos- ite, and compare features in the data. To lower the cost of segmentation, we show how partial region growing re- sults 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 e�ectiveness of the new visualization strategy that we have developed.