Auto-PCI: An approach to automated reading of single-pointer meters with adaptive ranges based on YOLOv5s and PP-OCRv3

Abstract In industry, pointer meters are still widely used in traditional industries to monitor the condition of equipment. However, most of the meter reading methods can only read specific gauges. For pointer meters with different ranges, we propose a range-adaptive method for automatic meter reading called Auto-PCI, which uses YOLOv5s to detect the scale values on the instrument panel, and PP-OCRv3 to read these values and determine the range of the target meter. Skewed meter images are corrected by perspective correction, combined with the use of U-Net to accurately extract the pointer and scale areas on the meter for accurate readings. Due to environmental factors, PP-OCRv3 may misread or fail to recognize meter scale values, so we propose a range estimation algorithm to improve the accuracy and stability of meter range recognition. Compared with existing methods, our method significantly improves the accuracy of readings with a 33.3% reduction in error.