In view of some problems in the traditional method of using Hough transform to identify the number of pointer meter, an improved reading method of pointer meter is proposed. Firstly, the algorithm corrects the tilt of the instrument image which can't be acquired due to the angle deviation. Through the comparison of several methods, it is proved that the proposed method is better. And according to the problem that directly using Hough transform to fit the pointer line will appear the influence of the border or other marks, which leads to the poor effect, the depth learning yolov5 model is introduced to realize the direct positioning of the pointer, so that the time required for line detection will be greatly reduced. After preprocessing the pointer image, image denoising, binarization and thinning, Hough linear transformation, angle method is used to realize the indicator recognition of pointer instrument. The experimental results show that the algorithm solves the limitation of the traditional recognition method, and the error between the recognition indication and the actual value of the pointer meter is - 2.73-3.64v, and the relative error is less than 2.47%, which meets the requirements of industrial meter reading.