Research on Defect Detection Method of Nonwoven Fabric Mask Based on Machine Vision

被引:0
|
作者
Huang, Jingde [1 ]
Huang, Zhangyu [2 ]
Zhan, Xin [1 ]
机构
[1] Zhuhai Coll Sci & Technol, Sch Mech Engn, 8 Anji East Rd, Zhuhai 519041, Peoples R China
[2] Macau Univ Sci & Technol, Fac Innovat Engn, Ave Wai Long, Taipa 999078, Macau, Peoples R China
关键词
Nonwoven fabric mask; machine vision; image processing; edge extraction; defect detection; FRAMEWORK; PREDICTION; ALGORITHMS;
D O I
10.1142/S021800142355008X
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
During the production, transportation and storage of nonwoven fabric mask, there are many damages caused by human or nonhuman factors. Therefore, checking the defects of nonwoven fabric mask in a timely manner to ensure the reliability and integrity, which plays a positive role in the safe use of nonwoven fabric mask. At present, the wide application of machine vision technology provides a technical mean for the defect detection of nonwoven fabric mask. On the basis of the pre-treatment of the defect images, it can effectively simulate the contour fluctuation grading and gray value change of the defect images, which is helpful to realize the segmentation, classification and recognition of nonwoven fabric mask defect features. First, in order to accurately obtain the image information of the nonwoven fabric mask, the binocular vision calibration method of the defect detection system is discussed. On this basis, the defect detection mechanism of the nonwoven fabric mask is analyzed, and the model of image processing based on spatial domain and Hough transform is established, respectively. The original image of the nonwoven fabric mask is processed by region processing and edge extraction. Second, the defect detection algorithm of nonwoven fabric mask is established and the detection process is designed. Finally, a fast defect detection system for nonwoven fabric mask is designed, and the effectiveness of the detection method for nonwoven fabric mask is analyzed with an example. The results show that this detection method has positive engineering significance for improving the detection efficiency of defects in nonwoven fabric mask.
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页数:21
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