Segmentation of measured point data using a parametric quadric surface approximation

Abstract

In reverse engineering, a shape containing multi-patched surfaces is digitized, the boundaries of these surfaces should be detected. The objective of this paper is to introduce a new and computationally efficient segmentation technique for extracting edges, and partitioning the 3D measured point data based on the location of the boundaries. The procedure begins with the identification of edge points. An automatic edge-based approach is developed on the basis of local geometry. A parametric quadric surface approximation method is used to estimate the local surface curvature properties. The least-square approximation scheme minimizes the sum of the squares of the actual Euclidean distance between the neighborhood data points and the parametric quadric surface. The surface curvatures and the principal directions are computed from the locally approximated surfaces. Edge points are identified as the curvature extremes, and zero crossings, which are found from the estimated surface curvatures. After edge points are identified, edge-neighborhood chain-coding algorithm is used for forming boundary curves. The original point set is then broken down into subsets, which meet along the boundaries, by scan line algorithm. All point data are applied to each boundary loops to partition the points to different regions. Experimental results are presented to verify the developed methods. (C) 1999 Elsevier Science Ltd. All rights reserved.