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.

Segmentation of secondary features from high-density acquired surfaces

Di Angelo, L.
;
Di Stefano, P.;
2017-01-01

Abstract

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.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/121008
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