Correction and pointer reading recognition of circular pointer meter

Abstract

For the meter images collected in the actual environment, there is the possibility of tilt and rotation. This paper presents a method to calibrate the circular pointer-type meter based on YOLOv5s network. The convolution neural network (CNN) framework is used to detect the scale value in the meter panel as the key point, the position information and value information of the detected scale value are used to fit the elliptic equation of the position of the scale value with the least square method for perspective correction and rotation correction of the meter, and the corrected meter image is used to obtain the meter pointer reading. This paper proposes the weighted angle method to read the meter reading. The accumulated error of the meter image after multiple transformations is eliminated. Finally, comparing the pointer detection method of this paper with the traditional pointer detection method, the error of this detection method is smaller; comparing the meter reading results before and after correction, the meter reading error after correction is 50\% less than before correction, and comparing the method of this paper with other mainstream methods, it proves the effectiveness of the correction method of this paper.

Application of Swin-Unet for pointer detection and automatic calculation of readings in pointer-type meters

“…Gao et al [50] designed a HOG multiclassification SVM numerical classifier that detected the gauge scale values, fitted the gauge pointer using the Progressive Probabilistic Hough Transform algorithm, and finally calculated the automotive dashboard readings using the angle between the scale values adjacent to the pointer. Ji et al [4] used a threshold segmentation method to obtain the pixel values in the root region of the pointer, and then determined the linear equation of the pointer by fitting an external ellipse to the region. However, this method needs to calculate the optimal segmentation threshold for each image when detecting the pointer, which is problematic in practical applications.…”

“…The complexity and the many workloads lead to fatigue at work, resulting in inaccurate readings and subjective assumptions. Manual readings are dangerous in some high altitude, high radiation, high temperature and high pressure environments [4]. Our research work, which focuses on rapidly and accurately obtaining automated readings from pointer-type meters in a variety of complex environments, is of research interest for practical applications.…”

Reading recognition of pointer meters based on an improved UNet++ network

“…The dice loss function [35] is used to optimize a model's objective by directly maximizing the dice coefficient between the predicted and ground truth segmentation. It is expressed in equation (7):…”

“…Unlike traditional machine vision algorithms that require preprocessing of the image, this approach avoids that step, which simplifies the overall process and enhances efficiency. Ji et al [7] proposed a circular pointer meter calibration method based on the YOLOv5s network. Using the CNN framework, the scale value in the meter panel is detected as the key point.…”