The paper considers the issue of using a computer vision system to control the quality of products in the control algorithm of a mechatronic sorting station. Shoe products are chosen as an example. The developed system is based on machine learning methods for image recognition by segmentation. As a result, a neural network model was created, and a program was written for identifying and selecting objects using a camera for subsequent sorting of defective products. The program contains three modules: initialization for declaring all variables, models, classes, video stream from the camera; the main module, containing an internal loop for each segmented object; a subroutine for completing the work. The introduction of computer vision into the control algorithm increases the efficiency and flexibility of the quality control system, and improves the accuracy of measuring the parameters of objects for their subsequent sorting.

Keywords: mechatronic station, sorting, computer vision, image segmentation, neural network training, control algorithm