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A method for surface topography measurement using a new focus function based on dual-tree complex wavelet transform

  • Tianjin University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Surface topography measurement is an important tool widely used in many fields to determine the characteristics and functionality of a part or material. Among existing methods for this purpose, the focus variation method has proved high performance particularly in large slope scenarios. However, its performance depends largely on the effectiveness of focus function. This paper presents a method for surface topography measurement using a new focus measurement function based on dual-tree complex wavelet transform. Experiments are conducted on simulated defocused images to prove its high performance in comparison with other traditional approaches. The results showed that the new algorithm has better unimodality and sharpness. The method was also verified by measuring a MEMS micro resonator structure.

Original languageEnglish
Title of host publication2017 International Conference on Optical Instruments and Technology
Subtitle of host publicationOptoelectronic Measurement Technology and Systems
EditorsKexin Xu, Hai Xiao, Jigui Zhu, Hwa-Yaw Tam
PublisherSPIE
ISBN (Electronic)9781510617537
DOIs
StatePublished - 2018
Event2017 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Systems - Beijing, China
Duration: Oct 28 2017Oct 30 2017

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume10621
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference2017 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Systems
Country/TerritoryChina
CityBeijing
Period10/28/1710/30/17

Keywords

  • dual-tree complex wavelet transform
  • focus function
  • focus variation
  • surface topography measurement

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