Open AccessA Facial Approach for Detection of Irregularly Entangled Copper Wire during Twining by Machine Vision
Author(s) -
Yuhang Zhang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1550/3/032016
Subject(s) - hough transform , copper , computer vision , artificial intelligence , copper wire , computer science , set (abstract data type) , machine vision , image (mathematics) , materials science , optics , physics , metallurgy , programming language
In this study, a computer vision-based inspection system is designed to detect the presence of irregularly entangled copper wire during twining for industrial processing. With the assistance of high speed industrial camera, the images of copper wire during twining would be recorded in real-time. All lines in the images are detected by Hough transform. According to the calculated slope of all lines detected in the images, a threshold is artificially set to distinguish between the regularly coiled and irregularly entangled copper wire. This defect detection system could greatly improve the efficiency of industrial production.