The aim of this paper is to present the application of computer vision in the process of automatic quality control of the final product. Quality control is a very important factor in an industry where automation is sought to speed up processes and reduce the possibility of human error. Computer vision allows the detection of errors or irregularities in high accuracy. The theoretical part of the paper describes the history and certain technologies of computer vision, it also describes the application of computer vision in different parts of the industry. In the first example of the experimental part, one of the ways of recognizing differences in two images using standard processing tools is demonstrated. Artificial intelligence for the needs of computer vision was developed with the help of convolutional neural networks and the presentation is in second example of the experimental part. For the purposes of this paper, the Python programming language and libraries such as OpenCV, Numpy and Keras were used for processing, image manipulation and learning of the neural network.