Water Meter Reading Area Detection Based on Convolutional Neural Network

Abstract

The water meter is a device for measuring the amount of water used by each household. Remote meter reading is one of the main ways to solve the waste of human resources caused by regular manual door-to-door access to mechanical water meter readings. The current use of image acquisition and then accurate reading of the water meter image is one of the ways of remote meter reading. In this paper, the convolutional neural network is used to predict the reading area, and then the non-maximum suppression algorithm (NMS) is used to remove highly overlapping results from prediction region results to obtain the position of the reading area. The experimental results show that with using the method proposed in this paper in the actual application scenario, the IoU of the images of 1000 test sets are all above 0.8 and then combined with the three-layer BP neural network for character recognition, the accuracy rate reaches 98.0%.