At present, many bearing production lines use manual naked eyes to identify the bearing workpiece number, which not only has poor recognition effect but also has low efficiency. In this study, a bearing embossing character recognition algorithm based on machine vision is designed, which is beneficial to bearing production and subsequent management. Firstly, the noise of the collected image is reduced by Gaussian filtering to reduce the influence of noise on the subsequent operation, and then the least square method is used to extract the ROI ring to determine the image region to be operated. Then the 1/8 circle scanning method is used to expand the ring image to make the character recognition operation more concise; then the character is segmented and normalized; finally, the character is recognized by SVM. The experimental results show that this method can realize bearing imprint character recognition, the recognition accuracy is more than 98%, and has good robustness, the system response speed is fast, and can meet the needs of industry.