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Chinese Journal of Lasers, Volume. 46, Issue 8, 0804002(2019)

Automatic Extraction and Classification of Road Markings Based on Deep Learning

Gang Huang1,2、* and Xianlin Liu3
Author Affiliations
  • 1 College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China
  • 2 Beijing GEO-Vision Tech. Co., Ltd., Beijing 100070, China
  • 3 Chinese Academy of Surveying & Mapping, Beijing 100830, China;
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    AbstractGet PDF(in Chinese)
    Figures&Tables (8)
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    References (24)
    Cited By (14)
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    Figures & Tables(8)
    Vehicle-borne mobile measurement system

    Fig. 1. Vehicle-borne mobile measurement system

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    Flow chart of automatic extraction and classification for road markings

    Fig. 2. Flow chart of automatic extraction and classification for road markings

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    Structure of Deeplab V3+

    Fig. 3. Structure of Deeplab V3+

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    Sample production. (a) Intensity characteristic image; (b) labeled image

    Fig. 4. Sample production. (a) Intensity characteristic image; (b) labeled image

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    Validation results

    Fig. 5. Validation results

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    Road marking vectorization. (a) Classification results; (b) clustering; (c) vectorization

    Fig. 6. Road marking vectorization. (a) Classification results; (b) clustering; (c) vectorization

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    • Table 1. Accuracy of automatic extraction and classification

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      Table 1. Accuracy of automatic extraction and classification

      ClassificationAccuracy /%
      Mesh88.17
      Sidewalk94.34
      Entrance86.51
      Arrow90.83
      Deceleration vertical81.47
      Deceleration horizontal76.36
      Mark77.62
      Longsolid95.73
      Dotted91.67
      Transverse92.35
      MIoU85.47

    • Table 2. Comparison of different methods

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      Table 2. Comparison of different methods

      MethodRPrecision /%RCompleteness /%Fscore /%
      Ref.[2]77.0353.7963.34
      Ref.[13]93.2773.8682.44
      Ref.[23]74.2966.5370.20
      Proposed92.5987.8490.15
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    Gang Huang, Xianlin Liu. Automatic Extraction and Classification of Road Markings Based on Deep Learning[J]. Chinese Journal of Lasers, 2019, 46(8): 0804002

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    Paper Information

    Category: measurement and metrology

    Received: Feb. 26, 2019

    Accepted: Apr. 2, 2019

    Published Online: Aug. 13, 2019

    The Author Email: Huang Gang (hgminisar@163.com)

    DOI:10.3788/CJL201946.0804002

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology