CAD mesh model segmentation by clustering

CAD mesh models have been widely employed in current CAD/CAM systems, where it is quite useful to recognize the features of the CAD mesh models. The first step of feature recognition is to segment the CAD mesh model into meaningful parts. Although there are lots of mesh segmentation methods in literature, the majority of them are not suitable to CAD mesh models. In this paper, we design a mesh segmentation method based on clustering, dedicated to the CAD mesh model. Specifically, by the agglomerative clustering method, the given CAD mesh model is first clustered into the sparse and dense triangle regions. Furthermore, the sparse triangle region is separated into planar regions, cylindrical regions, and conical regions by the Gauss map of the triangular faces and Hough transformation; the dense triangle region is also segmented by the mean shift operation performed on the mean curvature field defined on the mesh faces. Lots of empirical results demonstrate the effectiveness and efficiency of the CAD mesh segmentation method in this paper.

Graphical AbstractSegmentation result of a CAD mesh model.Figure optionsDownload high-quality image (118 K)Download as PowerPoint slideHighlights
► The CAD mesh model is classified into sparse and dense regions by the agglomerative hierarchical clustering method.
► The sparse region is partitioned into planar, cylindrical, and conical regions by the Gauss map and randomized Hough transformation.
► The dense region is segmented by performing the mean shift operation on the mean curvature field.