模式分析和计量:从可观察的测量中提取稳定特征

P. Scott
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引用次数: 86

摘要

为了从可观测测量中提取模式,我们需要能够定义和识别可观测测量中的稳定特征,这些特征在存在小的人工特征(如噪声、测量误差等)的情况下仍然存在。测量的表征理论被用来定义测量过程的稳定性。一种技术,“母题分析”,被定义为识别和删除“无关紧要”的特征,同时留下“重要”的特征。该技术是形式化的,并且确定了确保稳定性的三个属性。建立了基序分析与形态闭合滤波器之间的联系,并证明了基序分析的稳定性。最后,给出了表面纹理基序分析的计量实例。在这里,基序分析被用来将一个表面分割成它的重要特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pattern analysis and metrology: the extraction of stable features from observable measurements
To extract patterns from observable measurements we need to be able to define and identify stable features in observable measurements that persist in the presence of small artificial features such as noise, measurement errors, etc. The representational theory of measurement is used to define the stability of a measurement procedure. A technique, ‘motif analysis’, is defined to identify and remove ‘insignificant’ features while leaving ‘significant’ features. This technique is formalized and three properties identified that ensure stability. The connection of motif analysis with morphological closing filters is established and used to prove the stability of motif analysis. Finally, a practical metrology example is given of motif analysis in surface texture. Here motif analysis is used to segment a surface into its significant features.
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期刊介绍: Proceedings A publishes articles across the chemical, computational, Earth, engineering, mathematical, and physical sciences. The articles published are high-quality, original, fundamental articles of interest to a wide range of scientists, and often have long citation half-lives. As well as established disciplines, we encourage emerging and interdisciplinary areas.
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