Boundary fitting for 2D curve reconstruction

In this paper we present a 3-step algorithm for reconstructing curves from unorganized points: data clustering to filter out the noise, data confining to get the boundary, and region thinning to find the skeleton curve. The method is effective in removing far-from-the-shape noise and in handling a shape of changing density. The algorithm takes O(nlog n) time and O(n) space for a set of n points.