Open AccessApplication of Weighted Object Variance Algorithm in Metal Surface Defect Detection
Author(s) -
Wanzhi Zhang,
Juan Du,
Xingqiang Li,
Wei Wang
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/612/3/032143
Subject(s) - surface (topology) , variance (accounting) , object (grammar) , algorithm , feature (linguistics) , process (computing) , computer science , artificial intelligence , pattern recognition (psychology) , support vector machine , computer vision , mathematics , geometry , linguistics , philosophy , accounting , business , operating system
In the process of metal surface defect detection, it is difficult to detect and segment small defects. In order to solve this problem, this paper uses weighted object variance algorithm to detect metal surface defects. Then the feature of defect area is extracted and the defect classification model based on support vector machine is trained. In order to verify the effectiveness of the method, this paper takes the metal surface of bearing cylindrical roller as the specific research object. The experimental results show that the method meets the production requirements.