DEFECT DETECTION OF PRINTED FABRIC BASED ON RGBAAM AND IMAGE PYRAMID

被引:8
|
作者
Jing, Junfeng [1 ]
Ren, Huanhuan [1 ]
机构
[1] Xian Polytech Univ, Sch Elect Informat, Xian 710048, Shaanxi, Peoples R China
关键词
RGBAAM; Gaussian pyramid; periodic segmentation; defect detection;
D O I
10.2478/aut-2020-000
中图分类号
TB3 [工程材料学]; TS1 [纺织工业、染整工业];
学科分类号
0805 ; 080502 ; 0821 ;
摘要
To solve the problem of defect detection in printed fabrics caused by abundant colors and varied patterns, a defect detection method based on RGB accumulative average method (RGBAAM) and image pyramid matching is proposed. First, the minimum period of the printed fabric is calculated by the RGBAAM. second, a Gaussian pyramid is constructed for the template image and the detected image by using the minimum period as a template. Third, the similarity measurement method is used to match the template image and the detected image. Finally, the position of the printed fabric defect is marked in the image to be detected by using the Laplacian pyramid restoration. The experimental results show that the method can accurately segment the printed fabric periodic unit and locate the defect position. The calculation cost is low for the method proposed in this article.
引用
收藏
页码:135 / 141
页数:7
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