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Machine Intelligence Research

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01.02.2013

Robust Filtration Techniques in Geometrical Metrology and Their Comparison

verfasst von: Shan Lou, Wen-Han Zeng, Xiang-Qian Jiang, Paul J. Scott

Erschienen in: Machine Intelligence Research | Ausgabe 1/2013

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Abstract

Filtration is one of the core elements of analysis tools in geometrical metrology. Filtration techniques are progressing along with the advancement of manufacturing technology. Modern filtration techniques are required to be robust against outliers, applicable to surfaces with complex geometry and reliable in whole range of measurement data. A comparison study is conducted to evaluate commonly used robust filtration techniques in the field of geometrical metrology, including the two-stage Gaussian filter, the robust Gaussian regression filter, the robust spline filter and morphological filters. They are compared in terms of four aspects: functionality, mathematical computation, capability and characterization parameters. As a result, this study offers metrologists a guideline to choose the appropriate filter for various applications.

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Titel: Robust Filtration Techniques in Geometrical Metrology and Their Comparison
verfasst von: Shan Lou
Wen-Han Zeng
Xiang-Qian Jiang
Paul J. Scott
Publikationsdatum: 01.02.2013
Verlag: Springer-Verlag
Erschienen in: Machine Intelligence Research / Ausgabe 1/2013
Print ISSN: 2731-538X
Elektronische ISSN: 2731-5398
DOI: https://doi.org/10.1007/s11633-013-0690-4

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