Frit is a dot matrix pattern consisting of densely arranged small black dots, which can be found around the edges of the auto windshield. In the process of frit printing and sintering, there may be some defects such as adhesion and deformity, which tend to be false detection or missed detection in manual detection. And that manual data is difficult to be collected for deep analysis. To solve this problem, this paper tries to use machine vision technology to extract the outline of the frit as the camera moving track. Then the PLC is used to control the movement of the two cameras to take the frit pictures in sections from the four edges of the windshield to catch the clear images of the little black dots. Finally, the YOLOv5s algorithm is used online to identify and locate the frit defects. Compared with other different algorithms, the YOLOv5s algorithm is proven to be superior and robust in frit defect detection.