# The Machine Vision Dial Automatic Drawing System--Based on CAXA Secondary Development
## 1 Introduction
### Research Status at Home and Abroad
#### 1.2.1 Research Status of Instrument Representation Number Recognition  
Currently, research on dial pointer recognition has been extensively conducted by scholars both domestically and abroad, and image processing is the most commonly used method [5]. For circular instrument recognition, the Hough circle transform is mainly utilized to extract the outline of the dial, followed by the Hough line transformation to extract the pointer and corresponding reference line, enabling the current pointer indicator to be determined according to the straight line angle [6]. [PERSON] et al. [7] proposed a reading recognition method based on an improved Hough transform and adopted an improved adaptive median filtering method to obtain better image filtering results. The linear relationship between the scale of the instrument panel and the angle was used to determine the reading of the pointer. [PERSON] [8] extracted the dial image and eliminated background interference through OTSU threshold segmentation. The position of the dial circle was located through Hough circle detection, and the image was expanded to extract the pointer. [PERSON] et al. [9] from Hunan University proposed an automatic mechanical watch measurement method based on machine vision technology to address the issues of low efficiency and poor accuracy in reading mechanical watches. The mask-icon network was utilized to extract the pointer area, and methods such as the Canny operator and RANSAC least square distance were used to calculate the angle relationship between the pointer and center line, significantly enhancing mechanical watch precision measurement efficiency. [PERSON] et al. [10] proposed an instrument recognition method based on template matching and Hough circle detection. First, the position and \begin{table}
\begin{tabular}{c c c} \hline
**Type** & **Parameter** & **Remark** \\ \hline Product diameter \(\times\) height (mm) & 100 \(\times\) 200 & \\ Dial diameter (mm) & 88 & \\ Range (MPa) & \(-\)0.1–0.9 & \(-\)0.1 tick mark unchanged \\ Output mode & RS485 & \\ interface & M20 \(\times\) 1.5 & \\ Rated pressure/Pn (MPa) & 0.5 & Tested when blood pressure reduction is required \\ Low pressure closing pressure/Pa (MPa) & 0.45 & Tested when blood pressure reduction is required \\ Low pressure alarm pressure/Pv & & Tested when blood pressure reduction is required \\ \hline \end{tabular}
\end{table} 
Table 1: Product parameters of MKZB-IP SF6 density controller. center coordinates of the circular dial were obtained through the Hough circle detection method, followed by binarization of the image through the K-means method, and finally, the pointer was fitted and recognized through the rotating virtual line method. The reading was calculated based on the correspondence between the angle and the scale. Although the above-mentioned methods can realize the angle recognition of instrument pointers, the detection accuracy of the instrument described in this paper cannot meet actual production requirements. With the development of deep learning technology, scholars have utilized this method to achieve recognition of meter pointer reading and angle. [PERSON] et al. [11] used the convolutional neural network method to automatically extract character image features by designing network parameters, training the classification model, and finally utilizing the trained classification model to complete instrument character recognition. [PERSON] [12] proposed a convolutional neural network pointer meter image readout recognition method based on an attention mechanism, which constructs a two-way heterogeneous convolutional neural network that integrates convolutional attention modules and adopts a soft interval hierarchical regression to simplify the model volume. [PERSON] [13] improved the recognition method of pointer representation using the Hough transform and proposed a new pointer meter reading method. The deep learning yolov5 model was introduced to achieve direct positioning of the pointer.