Feature partitioning is one of the most frustrating problems in measurement processes. Currently the solution relies on technician's skills and experience but industries and metrological laboratories are searching for more rigorous procedures. The Geometrical Product Specification (GPS) project, whose goal is the formulation of a unique, coherent and mathematical-based framework for product shape control, is facing the problem. According to the mathematical approach adopted several years ago, the ISO/TC213, sponsor of the GPS project, proposed a classification of three-dimensional surfaces according to their invariance properties under the action of rigid motions (i.e. symmetries). This methodology requires the development and implementation of proper algorithms for feature classification and several approaches has been developed to partition surfaces on the basis of symmetries detection. Currently three different methods, available in scientific literature, are investigated to address the feature partitioning process: the Stanford method, the Wien method and the Turin method. Many other methods are available to solve the partitioning problem but only these methods rely on the feature classification adopted in the ISO/TC213 GPS project.

Shape Partitioning Based on Symmetries Detection / Chiabert, Paolo; Ruffa, Suela. - In: INTERNATIONAL JOURNAL OF SHAPE MODELING. - ISSN 0218-6543. - 14:(2008), pp. 79-104. [10.1142/S0218654308001075]

Shape Partitioning Based on Symmetries Detection

CHIABERT, Paolo;RUFFA, SUELA
2008

Abstract

Feature partitioning is one of the most frustrating problems in measurement processes. Currently the solution relies on technician's skills and experience but industries and metrological laboratories are searching for more rigorous procedures. The Geometrical Product Specification (GPS) project, whose goal is the formulation of a unique, coherent and mathematical-based framework for product shape control, is facing the problem. According to the mathematical approach adopted several years ago, the ISO/TC213, sponsor of the GPS project, proposed a classification of three-dimensional surfaces according to their invariance properties under the action of rigid motions (i.e. symmetries). This methodology requires the development and implementation of proper algorithms for feature classification and several approaches has been developed to partition surfaces on the basis of symmetries detection. Currently three different methods, available in scientific literature, are investigated to address the feature partitioning process: the Stanford method, the Wien method and the Turin method. Many other methods are available to solve the partitioning problem but only these methods rely on the feature classification adopted in the ISO/TC213 GPS project.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/1905912
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