[1]PANG Zengzhi,ZHENG Xiunan,LI Jinping.Research status of defect detection in X-ray images of all-steel radial tires[J].CAAI Transactions on Intelligent Systems,2019,14(4):793-803.[doi:10.11992/tis.201806014]
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Research status of defect detection in X-ray images of all-steel radial tires

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 14 Number of periods: 2019 4 Page number: 793-803 Column: 综述 Public date: 2019-07-02
Title:
Research status of defect detection in X-ray images of all-steel radial tires
Author(s):
PANG Zengzhi1; 2; 3;  ZHENG Xiunan1; 2; 3;  LI Jinping1; 2; 3
1. School of Information Science and Engineering, University of Ji’nan, Ji’nan 250022, China;
2. Shandong Provincial Key Laboratory of Network Based Intelligent Computing (University of Ji’nan), Ji’nan 250022, China;
3. Shandong College and University Key Laboratory of Information Processing and Cognitive Computing in 13th Five-year, Ji’nan 250022, China
Keywords:
all-steel radial tires; X-ray images; defect detection; image processing; machine learning; dictionary learning; Fourier transformation; Gabor transformation
CLC:
TP391
DOI:
10.11992/tis.201806014
Abstract:
All-steel radial tires have complex structures and there may be many defects in their production process. Image processing technology can be used to detect the defects of all-steel radial tires in X-ray images. In order to better sort out the existing algorithms, we have conducted research into the current defect detection algorithms for X-ray images of all-steel radial tires. First, we studied the current status and development history of defect detection for all-steel radial tires. We then classified the defects of all-steel radial tires, and made an introduction to the main detection methods for these defects according to different defect types, and analyzed their advantages and disadvantages. Finally, we pointed out the challenges in future research and look forward to the development direction of defect detection technology.
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