Machine vision [1-2] is a branch of artificial intelligence that measures and judges by computers replacing the human eyes. Machine vision recognition technology has the advantages of high speed, high precision and high robustness, which can meet the real-time requirements of industrial production and achieve accurate identification of product model. In this paper, an automatic identification system of wheel model is designed by using image processing technology and machine vision technology. The system converts the acquired target image information into digital signal through industrial camera, and then the computer program processes the acquired image through template matching algorithm. Calculation results determine the model of the target wheel, and finally automatic sorting of the wheel is achieved by the PLC system. The experiments prove that the wheel model automatic identification system has high accuracy and good stability. Meanwhile, the system meets the real-time performance of industrial production.
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Research on the Wheel Model Automatic Identification System
Semantic Scholar · Engineering · 2019
Abstract
Machine vision [1-2] is a branch of artificial intelligence that measures and judges by computers replacing the human eyes. Machine vision recognition technology has the advantages of high speed, high precision and high robustness, which can meet the real-time requirements of industrial production and achieve accurate identification of product model. In this paper, an automatic identification system of wheel model is designed by using image processing technology and machine vision technology. The system converts the acquired target image information into digital signal through industrial camera, and then the computer program processes the acquired image through template matching algorithm. Calculation results determine the model of the target wheel, and finally automatic sorting of the wheel is achieved by the PLC system. The experiments prove that the wheel model automatic identification system has high accuracy and good stability. Meanwhile, the system meets the real-time performance of industrial production.