Robust Filtration Techniques in Geometrical Metrology and Their Comparison

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 r...

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Bibliographic Details
Published in国际自动化与计算杂志 Vol. 10; no. 1; pp. 1 - 8
Main Author Shan Lou Wen-Han Zeng Xiang-Qian Jiang Paul J. Scott
Format Journal Article
LanguageChinese
Published 2013
Subjects
几何形状
分析工具
制造技术
形态学滤波器
技术进展
计量
过滤技术
高斯滤波器
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ISSN1476-8186
1751-8520

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Summary: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.
Bibliography:Geometrical metrology； robust Gaussian regression filter； robust spline filter； morphological filters； surface roughness
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.
11-5350/TP
ISSN:1476-8186
1751-8520