Currently, the vast majority of visual inspection software in the world wide market are traditional algorithms, not AI algorithms, commonly known as forward comparison. By inputting good product data and comparing it with other products, those that are different are considered non-conforming products. Traditional algorithms are algorithm standards established based on the first generation of measurement data, which detect product matching and adapt to software. The software has pre-set various defect modules, and on-site operators circle different defect modules to different positions of the product for detection. As the detected product moves rapidly through the detection camera, the detection position may deviate to varying degrees. Therefore, the software needs to continuously adjust the detection position on the detected product through circle drawing to provide detection accuracy. The adjusted parameters are complex, the operation is locked, and the technical requirements for operators are high. It is also susceptible to interference, misjudgment, and missed detection due to the influence of the product's external structure.

Technical advantages:
Suitable for measurement and positioning needs, with high measurement accuracy;

Technical disadvantages:
1. The program parameters are numerous and complex, and there are often correlations between parameters, which heavily rely on the experience of professional debugging personnel;
2. Developing algorithms specifically for special needs requires a long development cycle and cannot quickly add algorithm models;
3. There is no fast algorithm for complex requirements, resulting in low computational efficiency and a single type of defect detection;
4. High requirements for operating conditions and poor environmental adaptability;