Abstract
Starting from areal surface topography data as provided by current commercial three-dimensional (3D) profilometers and 3D digital microscopes, this work investigates the problem of automatically identifying and extracting functionally relevant, individual features within the acquisition area. Feature identification is achieved by adopting an original template-matching algorithmic procedure, based on applying the ring projection transform in combination with a parametric template. The proposed algorithmic procedure addresses in particular template-matching scenarios where significant variability may be associated with the features to be compared to the reference template. The algorithm is applied to a test case involving the characterization of the surface texture of a superabrasive polishing tool used in hard-disk manufacturing.
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