Qingzhi Yang1, Xiao Yu2, and Qun Chen  3

1Department of Intelligent Engineering, Bozhou Vocational and Technical College, Bozhou 236800, China
2Anhui Lianpeng Bottle Caps Packaging Co. Ltd., Bozhou 236800, China
3College of Pharmacy, Bozhou Vocational and Technical College, Bozhou 236800, China


Received: December 10, 2021
Accepted: June 23, 2022
Publication Date: July 20, 2022

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

Download Citation: ||https://doi.org/10.6180/jase.202304_26(4).0005  


Defects in liquor and medicine bottlecaps are difficult to be detected by common intelligent vision inspection equipment due to their complex shapes. Manual testing is highly dependent on the subjective judgment of workers, so it is hard to guarantee the test quality. Based on machine vision recognition, this paper construct an online defect detection system with LED light source, industrial camera, industrial computer and PLC for drugs and liquor caps. According to the test results, the system operation is stable and reliable, achieving the design purpose.

Keywords: machine vision; defect detection; image segmentation; grayscale; contour tracking; edge algorithm


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