A New Approach of Seed-Set Finding for Iso-Surface Extraction

Iso-surface extraction is one of the most important approaches for volume rendering, and iso-contouring is one of the most effective methods for iso-surface extraction. Unlike most other methods having their search domain to be the whole dataset, iso-contouring does its search only on a relatively small subset of the original data-set. This subset, called a seed-set, has the property that every iso-surface must intersect with it, and it could be built at the preprocessing time. When an iso-value is given at the run time, isocontouring algorithm starts from the intersected cells in the seedset, and gradually propagates to form the whole iso-surface. As smaller seed-sets offer less cell searching time, most existing isocontouring algorithms concentrate on how to identify an optimal seed-set. In this paper, we propose a new and efficient approach for seed-set construction. This presented algorithm could reduce the size of the generated seed-sets by up to one order of magnitude, compared with the volume thinning approach.