Research on the method of quickly identifying and reading pointer meter

Abstract

Aiming at the problems of poor detection results and low reading accuracy caused by small targets and oblique shooting angles of pointer instruments in complex background environments, a combined method of depth learning, perspective transformation, and Canny edge detection was proposed to perform pointer instrument readings. This recognition method uses an improved YOLO V7 target detection algorithm to detect and extract instruments in complex environments, and then corrects the extracted instruments through perspective transformation. Finally, the Canny edge detection algorithm and Hough transform are used to determine the center and pointer characteristics to obtain pointer readings. Through experimental comparison and verification, this method is more accurate and reliable than traditional methods, with a certain speed. It provides a more accurate and faster method for identifying pointer type instrument readings for subsequent work.