A comparitive study of image filters and machine learning for use in machined part recognition

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Abstract

The use of filters for image processing has long existed and is well established within industrial practice and in academia. The wide-spread adoption of machine learning into industrial spaces, however, has presented opportunities for the use of machine learning and artificial intelligence applications to be further developed and researched in relation to image processing. This paper aims to identify three of the main types of filters used in the machine learning process and to test their ability for target recognition of a basic/standard industry part.

Original languageEnglish
Title of host publication2019 13th International Conference on Sensing Technology, ICST 2019
PublisherIEEE Computer Society
ISBN (Electronic)9781728146317
DOIs
Publication statusPublished - Dec 2019
Event13th International Conference on Sensing Technology, ICST 2019 - Sydney, Australia
Duration: 2 Dec 20194 Dec 2019

Publication series

NameProceedings of the International Conference on Sensing Technology, ICST
Volume2019-December
ISSN (Print)2156-8065
ISSN (Electronic)2156-8073

Conference

Conference13th International Conference on Sensing Technology, ICST 2019
Country/TerritoryAustralia
CitySydney
Period2/12/194/12/19

Keywords

  • Canny
  • Edge detector
  • Filter
  • Filtering
  • Gaussian
  • Greyscale
  • Smoothing

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