CONSTRUCTING IMPLICIT SHAPE MODELS FROM BOUNDARY DATA

We develop a method to construct an implicit shape model that approxim ates a solid object from its characteristic function. The method is ba sed on multiresolution edge detection and reconstruction using dyadic wavelets. It synthesizes edges at multiple resolutions such that the r econstructed function preserves the shape boundary, and the gradient o f the function gives the normal vector field at the boundary. Several examples and applications of the procedure are given. One of the appli cations consists of the procedure of obtaining a rough estimate of the tubular neighborhood of a shape. We also apply this procedure to obta in an approximate, but accurate, conversion from a parametric to an im plicit surface. (C) 1995 Academic Press,Inc.