Identifying defects on a surface of a product
Visual AI can be used to identify defects on a product surface by using techniques such as image processing, pattern recognition, and machine learning. This can be done by capturing an image of the product surface, pre-processing the image to remove noise and improve contrast, then using algorithms to detect any anomalies or defects that deviate from a standard pattern. Some common defects that can be detected include scratches, cracks, chips, and blemishes. The results can be used for quality control and to improve the manufacturing process.