Automatic inspection and reading system of pointer instrument based on computer vision

Abstract

Aiming at the problems of background interference and incorrect angles in the images collected by inspection robots, a computer vision-based automatic inspection and reading system for pointer-type instruments is proposed, which can automatically obtain pointer readings on the basis of instrument image detection and correction. First, use the Centernet algorithm to detect the target of the pointer instrument image, and cut out the instrument image with the background removed according to the detected position information; then, perform key point detection, select a pair of symmetrical key points to rotate the instrument using affine transformation correction, and then select two pairs of symmetrical key points through template matching to correct the inclination of the meter using perspective transformation; finally, complete the reading of the meter by using Otsu segmentation and Hough transform circle and line detection. The experimental results show that the proportion of images to be corrected is 93%, the average error rate of the corrected instrument image is reduced by 10.19%, and the average accuracy of readings reaches 97.02%, which can meet the practical application.