Application of Computer Vision Technologies for Automated Utility Meters Reading

Maria Spichkova, Johan Van Zyl


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.


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