An ADMM-based scheme for distance function approximation
Alexander G. Belyaev, Pierre‐Alain Fayolle · Numerical Algorithms · 2019
Abstract A novel variational problem for approximating the distance function (to a domain boundary) is proposed. It is shown that this problem can be efficiently solved by ADMM. A review of several other variational and PDE-based methods for distance function estimation is presented. Advantages of the proposed distance function estimation method are demonstrated by numerical experiments. Applications of the method to the problems of surface curvature estimation and computing the skeleton of a binary image are shown.