Design of Industrial Machine Vision System Based on Improved Genetic Algorithm

In the stage of industrial production, assembly line is a very common production mode. In the assembly line, sorting operation is a very important link, which mainly classifies multiple types of materials or workpieces and puts them in corresponding positions according to the types of materials. It is the focus of robot research to apply vision system to industrial robots to make robots have the function of human eyes. In order to improve the sorting technology of robots, this article studies the construction of industrial robot sorting technology platform based on machine vision, and proposes an industrial machine vision recognition model based on improved genetic algorithm (GA). The results show that the algorithm has higher accuracy for machine vision recognition of industrial robots, which is 20.88% higher than that of wavelet transform algorithm, and can locate the edge contour of industrial production images more accurately. The sorting system can effectively solve the problem of classifying regular geometric workpieces and achieve the purpose of sorting. In robot sorting technology, the creation of machine vision is the basis for its successful sorting. Scientific research on robot machine vision can help robots work smoothly and quickly, improve work efficiency and promote the development of social and economic fields.