In many applications polygonal surfaces containing a large number of
primitives occur. Recently researchers have developed geometry
compression in order to reduce storage space and transmission time for
such models. A special case is given by isosurfaces generated from
gridded volume data. However, current state-of-the-art geometry
compression systems do not capitalize on the geometrical structure
that is characteristic of such isosurfaces, namely that the
surfaces are defined by a set of vertices on edges of the grid. We
propose a compression method for isosurfaces that is designed to
exploit this feature. We tested our method for several isosurfaces from a CT scan of a human head. In all cases our coder outperformed
state-of-the-art geometry compression methods by a factor of 2.2 to 2.8 in terms of compression ratio.
