At present, manual identification and registration of bicycle frame numbers are still used, which is labor-intensive and inefficient. If automatic optical identification (AOI) is used for character recognition, the stainless steel tube surface is a curved surface, and lighting is easy to cause reflection, making the The code on the curved surface is not clear. Whether manual or automatic optical inspection, it is more difficult to identify the characters on the curved, reflective stainless steel tube. Solomon combines machine vision and artificial intelligence to use SolVision Segmentation technology to train AI models for the gloss of the numbers on the stainless steel tube, which can achieve excellent optical character recognition results.