• Laser & Optoelectronics Progress
  • Vol. 57, Issue 20, 201507 (2020)
Huan Chi*
Author Affiliations
  • Department of Mechanical Engineering, Tianjin College, University of Science and Technology Beijing, Tianjin 301830, China
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    DOI: 10.3788/LOP57.201507 Cite this Article Set citation alerts
    Huan Chi. Online Detection Method of Woven Bag Defects Based on Machine Vision[J]. Laser & Optoelectronics Progress, 2020, 57(20): 201507 Copy Citation Text show less
    System block diagram
    Fig. 1. System block diagram
    Flow chart of defect detection algorithm
    Fig. 2. Flow chart of defect detection algorithm
    Preprocessing images.(a) Original hole image; (b) mean filtered image of hole; (c) gray close operation image of hole; (d) gray open operation image of hole; (e) original wire drawing; (f) close operation image of wire drawing; (g) original black thing; (h) close operation image of the black thing
    Fig. 3. Preprocessing images.(a) Original hole image; (b) mean filtered image of hole; (c) gray close operation image of hole; (d) gray open operation image of hole; (e) original wire drawing; (f) close operation image of wire drawing; (g) original black thing; (h) close operation image of the black thing
    Images of difference image binarization. (a) Hole image; (b) wire drawing; (c) black thing
    Fig. 4. Images of difference image binarization. (a) Hole image; (b) wire drawing; (c) black thing
    Diagram of defect detection results. (a) Close operation of the hole image; (b) open operation of the hole image; (c) close operation of the wire drawing; (d) close operation of the black thing
    Fig. 5. Diagram of defect detection results. (a) Close operation of the hole image; (b) open operation of the hole image; (c) close operation of the wire drawing; (d) close operation of the black thing
    Structural factor characteristic diagram
    Fig. 6. Structural factor characteristic diagram
    Feature maps. (a) Defects of small wire drawing; (b) defects of big wire drawing; (c) defects of hole; (d) defects of fold; (e) defects of the black thing
    Fig. 7. Feature maps. (a) Defects of small wire drawing; (b) defects of big wire drawing; (c) defects of hole; (d) defects of fold; (e) defects of the black thing
    Diagram of defect detection results
    Fig. 8. Diagram of defect detection results
    No.ConditionClassification
    1G≥5% and L≥100Big wire drawing
    2G≥5% and100>L≥30 and S>7Small wire drawing
    3G<5%Black stripes
    4G≥5% and 100>L≥30 and S≤7Black thing
    5A≥200 and 0.1≥D≥-0.5Hole
    6D<-0.5 or D>0.1Fold
    Table 1. Feature and defect classification matching table
    No.SpecieSampleSuccess numberError number
    1Nonconforming product40038911
    2Hole defects48462
    3Drawing defects52511
    Total50048614
    Table 2. Test classification results
    Huan Chi. Online Detection Method of Woven Bag Defects Based on Machine Vision[J]. Laser & Optoelectronics Progress, 2020, 57(20): 201507
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