Tires go through many high-pressure, high-load and high-temperature processes during the manufacturing process. The dust generated by the on-site machines and materials, coupled with the long-term operation of the printing process, make the surface of the inner tube blurry and the color shades uneven, affecting the recognition of the inner tube coding. After mass production, it is not conducive to manual recognition. If traditional AOI detection is used, it cannot be effectively identified in the case of unclear digital printing.Using Solomon SolVision's Segmentation technology, the numbers and shapes of the tire inner tube codes are photographed and trained for AI models. Then, optical character recognition (OCR) is used to accurately identify the codes. Even for incompletely printed or lightly colored characters, they can all be successfully identified, effectively improving the accuracy of code recognition.