Defect Straw Inspection Method Based on Machine Vision

被引:0
作者
Zhu, Ying [1 ]
Zhang, Hui [1 ]
Zhang, Zhisheng [1 ]
Xia, Zhijie [1 ]
机构
[1] Southeast Univ, SEU, Sch Mech Engn, Nanjing, Peoples R China
来源
2020 IEEE 3RD INTERNATIONAL CONFERENCE ON INFORMATION COMMUNICATION AND SIGNAL PROCESSING (ICICSP 2020) | 2020年
基金
中国国家自然科学基金;
关键词
straw defect; defect detection; machine vision; image processing; corner detection; ALGORITHM;
D O I
10.1109/icicsp50920.2020.9232102
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The visual inspection of defect straw can overcome the shortcomings of manual inspection, such as low accuracy, low efficiency, and poor real-time performance. It plays an important role in improving the production capacity and automation level of the enterprise. This paper takes telescopic straws as the research object, divides the defect types into global defects and local defects by analyzing the characteristics of each defect, and elaborate on the detection process and detection algorithm involved for each defect. A detection method from global to local is proposed by using image processing technology. In addition, this paper also proposes a new corner detection method, which has strong robustness to target corner detection in noisy images after experimental comparison. Finally, after experimental verification, the defect detection rate of the detection method proposed in this paper reached 98.8%.
引用
收藏
页码:198 / 202
页数:5
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