• Acta Optica Sinica
  • Vol. 39, Issue 2, 0212004 (2019)
Shengchun Wang1、*, Qiang Han1、2, Hao Wang1, Xinxin Zhao1, and Peng Dai1
Author Affiliations
  • 1 Infrastructure Inspection Research Institute, China Academy of Railway Sciences Corporation Limited, Beijing 100081, China
  • 2 School of Science, Beijing Jiaotong University, Beijing 100044, China
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    DOI: 10.3788/AOS201939.0212004 Cite this Article Set citation alerts
    Shengchun Wang, Qiang Han, Hao Wang, Xinxin Zhao, Peng Dai. Laser Stripe Center Extraction Method of Rail Profile in Train-Running Environment[J]. Acta Optica Sinica, 2019, 39(2): 0212004 Copy Citation Text show less
    Mirror reflection and image development
    Fig. 1. Mirror reflection and image development
    Effect of mirror reflection on stripe extraction. (a) Mirror reflection at headband; (b) binarization result of Fig. 2(a); (c) mirror reflection on polished rail; (d) binarization result of Fig. 2(c)
    Fig. 2. Effect of mirror reflection on stripe extraction. (a) Mirror reflection at headband; (b) binarization result of Fig. 2(a); (c) mirror reflection on polished rail; (d) binarization result of Fig. 2(c)
    Gray-level distribution characteristics of laser stripe. (a) Laser stripe image; (b) gray-level distribution of laser stripe; (c) local zoom of Fig. 3(a); (d) local zoom of Fig. 3(b)
    Fig. 3. Gray-level distribution characteristics of laser stripe. (a) Laser stripe image; (b) gray-level distribution of laser stripe; (c) local zoom of Fig. 3(a); (d) local zoom of Fig. 3(b)
    Extraction process of light stripe center line based on sub-region multi-template matching
    Fig. 4. Extraction process of light stripe center line based on sub-region multi-template matching
    Image segmentation performance statistics for different depth network structures [14]
    Fig. 5. Image segmentation performance statistics for different depth network structures [14]
    Rail profile data labeling
    Fig. 6. Rail profile data labeling
    Section partition of rail profile laser stripe
    Fig. 7. Section partition of rail profile laser stripe
    Gradient direction of pixels.(a) Gradient direction solved for whole image; (b) gradient direction solved only on segmented light stripe
    Fig. 8. Gradient direction of pixels.(a) Gradient direction solved for whole image; (b) gradient direction solved only on segmented light stripe
    Direction template corresponding to each sub-range of segmentation
    Fig. 9. Direction template corresponding to each sub-range of segmentation
    Extraction of pixel-level light stripe center based on direction template
    Fig. 10. Extraction of pixel-level light stripe center based on direction template
    Extraction of sub-pixel level light stripe center based on gray-level centroid method
    Fig. 11. Extraction of sub-pixel level light stripe center based on gray-level centroid method
    Image rotation and scaling
    Fig. 12. Image rotation and scaling
    Comparison of light stripe segmentation results. (a) Original rail profile image; (b) fixed threshold binarization; (c) dynamic threshold binarization; (d) deep learning segmentation results
    Fig. 13. Comparison of light stripe segmentation results. (a) Original rail profile image; (b) fixed threshold binarization; (c) dynamic threshold binarization; (d) deep learning segmentation results
    Convolution features of light stripe image. (a) Convolution feature of first layer with size of 16×256×256; (b) convolution feature of second layer with size of 64×128×128; (c) convolution feature of third layer with size of 128×164×164
    Fig. 14. Convolution features of light stripe image. (a) Convolution feature of first layer with size of 16×256×256; (b) convolution feature of second layer with size of 64×128×128; (c) convolution feature of third layer with size of 128×164×164
    Experimental results and corresponding local zoom for different laser stripe center extraction methods. (a) Gray-level centroid method[17]; (b) direction-template method [18]; (c) Steger method [19]; (d) proposed method
    Fig. 15. Experimental results and corresponding local zoom for different laser stripe center extraction methods. (a) Gray-level centroid method[17]; (b) direction-template method [18]; (c) Steger method [19]; (d) proposed method
    Precision comparison of different laser stripe center extraction methods
    Fig. 16. Precision comparison of different laser stripe center extraction methods
    Execution time comparison of different laser strip center extraction methods
    Fig. 17. Execution time comparison of different laser strip center extraction methods
    Image size /(pixel×pixel)800×600960×200480×100
    Time /ms12.36.41.8
    Frame rate /(frame·s-1)81156554
    Table 1. Segmentation time comparison of images with different sizes by ENet
    Shengchun Wang, Qiang Han, Hao Wang, Xinxin Zhao, Peng Dai. Laser Stripe Center Extraction Method of Rail Profile in Train-Running Environment[J]. Acta Optica Sinica, 2019, 39(2): 0212004
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