The hydrophobicity class of porcelain insulator detection based on digital image processing : A paper review

Conference proceedings article

Authors/Editors

Strategic Research Themes

Publication Details

Author list: Sonkaeo, Poohthip; Techawatcharapaikul, Chanchai

Publisher: Elsevier

Publication year: 2021

Start page: 759

End page: 762

Number of pages: 4

ISBN: 9780738111278

ISSN: 0928-4931

eISSN: 1873-0191

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112818198&doi=10.1109%2fECTI-CON51831.2021.9454864&partnerID=40&md5=e57d22463d27ef2149f978e9e7307985

Languages: English-Great Britain (EN-GB)

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Abstract

The experiment of quality assurance of polymeric outdoor insulators service life is necessary to be checked the class of wettability by using the digital image processing tools. The image processing can improve its pictorial information for human interpretation, render it more suitable for autonomous machine perception. This paper provides a survey of the recent technology and theoretical concept to explain the development of the Hydrophobicity Class (HC) of porcelain insulator. The hydrophobic properties of the housing material were found degraded to a different extent between field-aged insulators due to differences in material structure and pollution conditions. This paper contributes to the latest development of reviews relating to image processing for the implementation of porcelain insulator hydrophobic systems testing., and their related studies. We categorized the computer vision mainstream into 2 group such as Machine Learning Methods Applied to Digital Image Processing and Deep Learning Methods Applied to Digital Image Processing. Then compare pros/cons in each type of technique. We also provide brief explanation on the up-to-date information about the techniques and their performance. © 2021 IEEE.

Keywords

Hydrophobicity Class, image preprocessing