No abstract

The reconstruction of a surface model from a point cloud is an important task in the reverse engineering of industrial parts. We aim at constructing a curve network on the point cloud that will define the border of the various surface patches. In this paper, we present an algorithm to extract closed sharp feature lines, which is necessary to create such a closed curve network. We use a first order segmentation to extract candidate feature points and process them as a graph to recover the sharp feature lines. To this end, a minimum spanning tree is constructed and afterwards a reconnection procedure closes the lines. The algorithm is fast and gives good results for real-world point sets from industrial applications.

In reverse engineering, the reconstruction of a surface model from a point cloud requires the extraction of closed feature lines at the borders of the different surface patches. In this paper we propose a new algorithm to extract such closed polygonal feature lines, representing sharp or smooth edges, from a point cloud. Based on the variation of the normal vectors and a graph approach we extract the sharp edges, which are used to divide the point cloud in smooth regions. Smooth edges, such as fillets, are extracted for each smooth region separately using a novel approach for 1D-histogram thresholding: we use the curvature histogram in a multi-resolution manner in order to split a point set in different regions of similar curvature (patches). The polygonal smooth edges at the borders between these different patches are extracted by point clustering and processing a graph of the point clusters.