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Machine Vision Applied to Backscattered Electron Imaging

  • Junyuan Huang
  • , Wei Zhang*
  • , Jingyun Chen
  • *Corresponding author for this work
  • Beihang University
  • China Aerospace Science and Technology Corporation

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

Abstract

Electron beam processing usually needs to be carried out in a vacuum environment. The influence of high temperature and high concentration of metal vapor makes it difficult for traditional machine vision observation systems to perform long-Term observation. In this paper, a machine vision algorithm was used, a quadrupole plate sensor and image fusion algorithm were adopted, and the combination of software and hardware was realized. Finally, we solved the problems of scale imbalance and slice model scanning order in the imaging process and successfully realized clear observation of the surface in all directions. The backscattered electron signal imaging technology has been successfully applied to the electron beam processing process, which meets the online observation requirements of the electron beam processing process.

Original languageEnglish
Title of host publication2023 IEEE 6th International Conference on Pattern Recognition and Artificial Intelligence, PRAI 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages650-653
Number of pages4
ISBN (Electronic)9798350325485
DOIs
StatePublished - 2023
Event6th IEEE International Conference on Pattern Recognition and Artificial Intelligence, PRAI 2023 - Haikou, China
Duration: 18 Aug 202320 Aug 2023

Publication series

Name2023 IEEE 6th International Conference on Pattern Recognition and Artificial Intelligence, PRAI 2023

Conference

Conference6th IEEE International Conference on Pattern Recognition and Artificial Intelligence, PRAI 2023
Country/TerritoryChina
CityHaikou
Period18/08/2320/08/23

Keywords

  • Backscatter electron imaging
  • Electron beam processing
  • Machine vision

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