Combination of M-Estimation and Gaussian Filtering for Characterizing 3D Engineering Surfaces

H. F. Li; X. Q. Jiang; Z. Li

doi:10.4028/www.scientific.net/KEM.295-296.459

Combination of M-Estimation and Gaussian Filtering for Characterizing 3D Engineering Surfaces

H. F. Li, X. Q. Jiang, Z. Li

Research output: Contribution to journal › Article › peer-review

Abstract

A reliable reference is the key to characterize surface topography. Gaussian filtering is strongly recommended by experts in the international standardization field. However, it can be affected by abnormal surface features. Based on the principle of M-estimation, a novel robust weighting function is proposed to improve the Gaussian filtering and a 3D robust Gaussian filtering model is developed. Experimental results have proven them effective.

Original language	English
Pages (from-to)	459-464
Number of pages	6
Journal	Key Engineering Materials
Volume	295-296
DOIs	https://doi.org/10.4028/www.scientific.net/KEM.295-296.459
Publication status	Published - 15 Oct 2005
Externally published	Yes

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title = "Combination of M-Estimation and Gaussian Filtering for Characterizing 3D Engineering Surfaces",

abstract = "A reliable reference is the key to characterize surface topography. Gaussian filtering is strongly recommended by experts in the international standardization field. However, it can be affected by abnormal surface features. Based on the principle of M-estimation, a novel robust weighting function is proposed to improve the Gaussian filtering and a 3D robust Gaussian filtering model is developed. Experimental results have proven them effective.",

keywords = "Abnormal features, Gaussian filtering, M-estimation, Robust weighting function, Surface topography",

author = "Li, {H. F.} and Jiang, {X. Q.} and Z. Li",

year = "2005",

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AU - Jiang, X. Q.

AU - Li, Z.

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Y1 - 2005/10/15

N2 - A reliable reference is the key to characterize surface topography. Gaussian filtering is strongly recommended by experts in the international standardization field. However, it can be affected by abnormal surface features. Based on the principle of M-estimation, a novel robust weighting function is proposed to improve the Gaussian filtering and a 3D robust Gaussian filtering model is developed. Experimental results have proven them effective.

AB - A reliable reference is the key to characterize surface topography. Gaussian filtering is strongly recommended by experts in the international standardization field. However, it can be affected by abnormal surface features. Based on the principle of M-estimation, a novel robust weighting function is proposed to improve the Gaussian filtering and a 3D robust Gaussian filtering model is developed. Experimental results have proven them effective.

KW - Abnormal features

KW - Gaussian filtering

KW - M-estimation

KW - Robust weighting function

KW - Surface topography

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JF - Key Engineering Materials

SN - 1013-9826

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Combination of M-Estimation and Gaussian Filtering for Characterizing 3D Engineering Surfaces

Abstract

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