Quality inspection system for metal parts based on machine vision

Aiming at the problems of low accuracy and complex algorithm design for defect detection and dimensional measurement of metal parts, this paper designs a duplex inspection system using machine vision technology, which is connected to a multi-channel acquisition board and can achieve high efficiency in image acquisition and processing. The HALCON software is used to pre-process the images with algorithms such as threshold segmentation, morphological processing and image enhancement, and the MLP classifier is used to classify defects in the defect detection. The test results show that the system achieves high accuracy and high efficiency quality inspection, which brings some value to promote industrial automation and intelligent development.