Decreasing iso-surface complexity via discretized fitting

Since the introduction of standard techniques for isosurface extraction from volumetric datasets, one of the hardest problems has been to reduce the number of triangles (or polygons) generated. This paper presents an approximated algorithm that considerably reduces the number of polygons generated by a Marching Cubes-like scheme while presenting shorter running times. The algorithm assumes discretization of the dataset space and replaces cell edge interpolation by midpoint selection. Under these assumptions the extracted surfaces are composed of polygons lying within a finite number of incidences, thus allowing simple merging of the output facets into large coplanar triangular facets. An experimental evaluation of the proposed approach on datasets relevant to biomedical imaging and chemical modelling is reported.