Visual alignment system for PCB production based on yolov5

With the widespread popularity of electronic products, there is an urgent need for a fast and efficient accurate vision alignment system for PCB production. In order to improve the problem of insufficient accuracy and speed of the visual matching system, this paper designs an alignment system based on deep learning yolov5, which outlines the sensitive area including a large number of feature points through the preprocessing of the image taken by the industrial camera, thereby improving the production efficiency. Compared with Traditional gray-scale based image matching algorithm to prove Yolov5's high recognition rate and fast recognition speed in the detection environment of vision alignment system for PCB production.