Segmentation of secondary features from high-density acquired surfaces

A new method for secondary features segmentation, performed in highdensity acquired geometric models, is proposed. Four types of secondary features are considered: fillets, rounds, grooves and sharp edges. The method is based on an algorithm that analyzes the principal curvatures. The nodes, potentially attributable to a fillet of given geometry, are those with a certain value for maximum principal curvature. Since the deterministic application of this simple wor king principle shows several problems due to the uncertainties in the curvature estimation, a fuzzy approach is proposed. In order to segment the nodes of a tessellated model that pertain to the same secondary features, proper membership functions are evaluated as function of some parameters, which affect the quality of the curvature estimation. A region growing algorithm connects the nodes pertaining to the same secondary feature. The method is applied and verified for some test cases.