Open AccessResearch on straightness detection of steel strip edge based on machine vision
Author(s) -
Shuiping Li,
Chen Luo
Publication year - 2021
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 - 10.1088/1742-6596/1820/1/012063
Subject(s) - enhanced data rates for gsm evolution , strip steel , edge detection , computer vision , artificial intelligence , point (geometry) , canny edge detector , image (mathematics) , engineering , computer science , mathematics , image processing , geometry , mechanical engineering
In order to accurately detect the straightness of steel strip edge, a method of minimum containment area evaluation of straightness based on visual measurement scanning discriminant search is proposed. Firstly, opencv is used to preprocess the collected steel strip image, then Canny edge extraction operator is used to extract the steel strip edge, and the steel strip image contour is extracted. Finally, the straightness evaluation method proposed in this paper is used to measure the steel strip straightness. Compared with the measurement results of the two end point connection method and the least square method, the measurement results of the proposed straightness evaluation method are closer to the manual test results, which is conducive to improving the accuracy of steel strip straightness detection.