Quality inspection system for metal parts based on machine vision

Qixun Xiao; Shengquan Liang; Jingde Huang

doi:10.1117/12.2659356

22 November 2022 Quality inspection system for metal parts based on machine vision

Qixun Xiao, Shengquan Liang, Jingde Huang

Proceedings Volume 12475, Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022); 124750G (2022) https://doi.org/10.1117/12.2659356
Event: Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022), 2022, Hulun Buir, China

Abstract

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.

Citation Download Citation

Qixun Xiao, Shengquan Liang, and Jingde Huang "Quality inspection system for metal parts based on machine vision", Proc. SPIE 12475, Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022), 124750G (22 November 2022); https://doi.org/10.1117/12.2659356

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