• Laser & Optoelectronics Progress
  • Vol. 58, Issue 22, 2210001 (2021)
Liangfu Li, Nan Wang*, Biao Wu, and Xi Zhang
Author Affiliations
  • School of Computer Science, Shaanxi Normal University, Xi’an, Shaanxi 710119, China
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    DOI: 10.3788/LOP202158.2210001 Cite this Article Set citation alerts
    Liangfu Li, Nan Wang, Biao Wu, Xi Zhang. Segmentation Algorithm of Bridge Crack Image Based on Modified PSPNet[J]. Laser & Optoelectronics Progress, 2021, 58(22): 2210001 Copy Citation Text show less
    Low-quality image preprocessing. (a) Original image; (b) result obtained by Laplacian sharpening
    Fig. 1. Low-quality image preprocessing. (a) Original image; (b) result obtained by Laplacian sharpening
    Schematic of bridge crack dataset amplification. (a) Original image; (b) rotate 180°; (c) rotate 270°; (d) horizontal flip; (e) vertical flip
    Fig. 2. Schematic of bridge crack dataset amplification. (a) Original image; (b) rotate 180°; (c) rotate 270°; (d) horizontal flip; (e) vertical flip
    PSPNet structure
    Fig. 3. PSPNet structure
    Proposed network structure
    Fig. 4. Proposed network structure
    Schematic of the 3×3 convolution kernel receptive field with expansion rates of 1, 2, 3
    Fig. 5. Schematic of the 3×3 convolution kernel receptive field with expansion rates of 1, 2, 3
    SPAM structure
    Fig. 6. SPAM structure
    Loss curve during training
    Fig. 7. Loss curve during training
    Comparison results without and with SPAM. (a) Original image; (b) label; (c) without SPAM; (d) with SPAM
    Fig. 8. Comparison results without and with SPAM. (a) Original image; (b) label; (c) without SPAM; (d) with SPAM
    Comparison of results between different algorithms. (a) Original image; (b) label; (c) Deeplab-V3+; (d) U-Net++; (e) EncNet; (f) proposed algorithm
    Fig. 9. Comparison of results between different algorithms. (a) Original image; (b) label; (c) Deeplab-V3+; (d) U-Net++; (e) EncNet; (f) proposed algorithm
    SPAMPrecision /%Recall /%PA /%F1_score /%mIoU /%Time /s
    --86.1482.2598.2884.1576.340.46
    95.3490.2799.3792.7484.310.60
    Table 1. Comparison of experiment results without and with SPAM
    AlgorithmPrecision /%Recall /%PA /%F1_score /%mIoU /%Time /s
    U-Net++84.5280.1397.1482.2775.180.63
    Deeplab-V3+84.7681.4298.9383.0677.950.52
    EncNet91.3883.7999.0687.4280.750.42
    Proposed algorithm95.3490.2799.3792.7484.310.60
    Table 2. Comparison between the proposed algorithm and mainstream semantic segmentation models
    Liangfu Li, Nan Wang, Biao Wu, Xi Zhang. Segmentation Algorithm of Bridge Crack Image Based on Modified PSPNet[J]. Laser & Optoelectronics Progress, 2021, 58(22): 2210001
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