Application of Computer Vision Technologies for Automated Utility Meters Reading

Maria Spichkova, Johan Van Zyl

2020

Abstract

This paper presents a study on automated reading of utility meters using two computer vision techniques: an open-source solution Tensorflow Object Detection (Tensorflow) and a commercial solution Anyline. We aimed to identify the limitations and benefits of each solution applied to utility meters reading, especially focusing on aspects such as accuracy and inference time. Our goal was to determine the solution that is the most suitable for this particular application area, where there are several specific challenges.

Paper Citation

in Harvard Style

Spichkova M. and Van Zyl J. (2020). Application of Computer Vision Technologies for Automated Utility Meters Reading.In Proceedings of the 15th International Conference on Software Technologies - Volume 1: ICSOFT, ISBN 978-989-758-443-5, pages 521-528. DOI: 10.5220/0009892505210528

in Bibtex Style

@conference{icsoft20,
author={Maria Spichkova and Johan Van Zyl},
title={Application of Computer Vision Technologies for Automated Utility Meters Reading},
booktitle={Proceedings of the 15th International Conference on Software Technologies - Volume 1: ICSOFT,},
year={2020},
pages={521-528},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009892505210528},
isbn={978-989-758-443-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Software Technologies - Volume 1: ICSOFT,
TI - Application of Computer Vision Technologies for Automated Utility Meters Reading
SN - 978-989-758-443-5
AU - Spichkova M.
AU - Van Zyl J.
PY - 2020
SP - 521
EP - 528
DO - 10.5220/0009892505210528