### Abstract

In the measurement of microgeometrical surfaces it is useful if the same location can be found on a surface for two or more different and independent measurements, as in this case not only statistical parameters of the measurements can be compared, but direct differences can be calculated. Honing is a typical surface processing method resulting in pattern consisting of straight valleys crossing at various angles. Honing pattern is of great help to find a special location. The main goal of this article is to find a method that is able to give some characteristic points that can be used for fitting two measured surfaces together. Hough transform is used in finding straight lines in an image or map, thus it could be used for determining crossing points of the honed surface. However, classical Hough transform either finds way too many disturbing lines in the case of a typical honed surface or almost none, depending on the parameter selection. To solve this rapid changing in the number of the resulting lines, we introduced fuzzy Hough transform. If a fuzzified version of the weights of the individual points in the Hough transform is used, the inverse of the transform becomes clearer, resulting in a pattern more suitable for finding the same location on two measured versions of a surface.

Original language | English |
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Title of host publication | Studies in Computational Intelligence |

Publisher | Springer Verlag |

Pages | 35-42 |

Number of pages | 8 |

DOIs | |

Publication status | Published - Jan 1 2020 |

### Publication series

Name | Studies in Computational Intelligence |
---|---|

Volume | 819 |

ISSN (Print) | 1860-949X |

### Fingerprint

### Keywords

- Fuzzy sets
- Hough transform
- Microgeometrical surface analysis
- Pattern analysis

### ASJC Scopus subject areas

- Artificial Intelligence

### Cite this

*Studies in Computational Intelligence*(pp. 35-42). (Studies in Computational Intelligence; Vol. 819). Springer Verlag. https://doi.org/10.1007/978-3-030-16024-1_5

**Applying fuzzy hough transform for identifying honed microgeometrical surfaces.** / Nagy, S.; Solecki, Levente; Sziová, Brigita; Sarkadi-Nagy, Balázs; Kóczy, L.

Research output: Chapter in Book/Report/Conference proceeding › Chapter

*Studies in Computational Intelligence.*Studies in Computational Intelligence, vol. 819, Springer Verlag, pp. 35-42. https://doi.org/10.1007/978-3-030-16024-1_5

}

TY - CHAP

T1 - Applying fuzzy hough transform for identifying honed microgeometrical surfaces

AU - Nagy, S.

AU - Solecki, Levente

AU - Sziová, Brigita

AU - Sarkadi-Nagy, Balázs

AU - Kóczy, L.

PY - 2020/1/1

Y1 - 2020/1/1

N2 - In the measurement of microgeometrical surfaces it is useful if the same location can be found on a surface for two or more different and independent measurements, as in this case not only statistical parameters of the measurements can be compared, but direct differences can be calculated. Honing is a typical surface processing method resulting in pattern consisting of straight valleys crossing at various angles. Honing pattern is of great help to find a special location. The main goal of this article is to find a method that is able to give some characteristic points that can be used for fitting two measured surfaces together. Hough transform is used in finding straight lines in an image or map, thus it could be used for determining crossing points of the honed surface. However, classical Hough transform either finds way too many disturbing lines in the case of a typical honed surface or almost none, depending on the parameter selection. To solve this rapid changing in the number of the resulting lines, we introduced fuzzy Hough transform. If a fuzzified version of the weights of the individual points in the Hough transform is used, the inverse of the transform becomes clearer, resulting in a pattern more suitable for finding the same location on two measured versions of a surface.

AB - In the measurement of microgeometrical surfaces it is useful if the same location can be found on a surface for two or more different and independent measurements, as in this case not only statistical parameters of the measurements can be compared, but direct differences can be calculated. Honing is a typical surface processing method resulting in pattern consisting of straight valleys crossing at various angles. Honing pattern is of great help to find a special location. The main goal of this article is to find a method that is able to give some characteristic points that can be used for fitting two measured surfaces together. Hough transform is used in finding straight lines in an image or map, thus it could be used for determining crossing points of the honed surface. However, classical Hough transform either finds way too many disturbing lines in the case of a typical honed surface or almost none, depending on the parameter selection. To solve this rapid changing in the number of the resulting lines, we introduced fuzzy Hough transform. If a fuzzified version of the weights of the individual points in the Hough transform is used, the inverse of the transform becomes clearer, resulting in a pattern more suitable for finding the same location on two measured versions of a surface.

KW - Fuzzy sets

KW - Hough transform

KW - Microgeometrical surface analysis

KW - Pattern analysis

UR - http://www.scopus.com/inward/record.url?scp=85066127682&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85066127682&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-16024-1_5

DO - 10.1007/978-3-030-16024-1_5

M3 - Chapter

AN - SCOPUS:85066127682

T3 - Studies in Computational Intelligence

SP - 35

EP - 42

BT - Studies in Computational Intelligence

PB - Springer Verlag

ER -