The Energy Meter Translation by Optical Character Recognition Technique

Conference proceedings article

Authors/Editors

CHANCHAI TECHAWATCHARAPAIKUL

Strategic Research Themes

Digital Transformation (Strategic Research Themes)

Publication Details

Author list: Khunsamitpanya, Rungaroon; Yotsongpol, Rangsiman; Srichanpliuw, Sharunya; Techawatcharapaikul, Chanchai

Publisher: Hindawi

Publication year: 2021

Start page: 412

End page: 415

Number of pages: 4

ISBN: 9781730000000

ISSN: 0146-9428

eISSN: 1745-4557

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85107813305&doi=10.1109%2fiEECON51072.2021.9440304&partnerID=40&md5=62e9654c2e2ec2354f7973c4afbc7905

Languages: English-Great Britain (EN-GB)

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Abstract

This paper presented an automatic energy meter reading system using the OCR process. Results showed that the system can recognize the energy meter reading digits in only three processes with an accuracy of 91 %. The work presented in this paper is a valuably consequential idea to design an algorithm of the energy meter translation using Optical Character Recognition (OCR). © 2021 IEEE.

Keywords

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