Laser & Optoelectronics Progress, Volume. 56, Issue 8, 081006(2019)

Methodfor Orientation Determination of Transmission Line Tower Based on Visual Navigation

Zuwu Wang1,2、*, Jun Han1,2, Xiaobin Sun3, and Bo Yang3
Author Affiliations
  • 1 School of Communication and Information Engineering, Shanghai University, Shanghai 200444, China
  • 2 Shanghai Institute of Advanced Communications and Data Science, Shanghai 200444, China
  • 3 State Grid Shandong Electric Power Company, Jinan, Shandong 250000, China
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    Figures & Tables(14)
    Aerial images and diagrams of towers. (a) Front image; (b) front side image; (c) side image; (d) front view diagram; (e) front side view diagram; (f) side view diagram
    Broken lines formed when wire passing through straight tower
    Location relationship between guiding lines and wires in tensile tower
    Structural characteristics of tower. (a) Cross slanted segments of tower head; (b)(c) slanted segments converged onto main frame of tower body; (d)(e) crossing characteristics in tower
    Framework of tower detection from far to near
    Calculation of gradient for each pixel point
    Angular distribution of gradient
    Gradient statistical histogram in each cell
    HOG feature extraction and MLP perception model classification
    Visual perception platform for UAV and local areas of tower under different orientations. (a) Visual perception platform for UAV; (b1) front of tower top; (b2) front side of tower top; (b3) side of tower top; (c1) front of tower body; (c2) front side of tower body; (c3) side of tower body; (d1) front of tower bottom; (d2) front side of tower bottom; (d3) side of tower bottom
    • Table 1. Accuracy rate of identification of local area orientation of tower

      View table

      Table 1. Accuracy rate of identification of local area orientation of tower

      AlgorithmFig. 10 (b)Fig. 10 (c)Fig. 10 (d)
      FrontFront sideSideFrontFront sideSideFrontFront sideSide
      ZF-Net+Faster RCNN0.6820.6910.7020.6180.6990.6640.6770.6860.629
      VGG16+Faster RCNN0.7400.7240.7430.6410.7560.7510.7650.7310.763
      ResNet-101+Faster RCNN0.7720.7800.7880.6930.8010.7930.7870.7590.789
      HOG+MLP(Proposed)0.8260.8180.8590.8790.8910.9020.8780.8690.821
    • Table 2. Time required for identification of local area orientation of towerms

      View table

      Table 2. Time required for identification of local area orientation of towerms

      AlgorithmFig. 10 (b)Fig. 10 (c)Fig. 10 (d)
      FrontFront sideSideFrontFront sideSideFrontFront sideSide
      ZF-Net +Faster RCNN313329263037293331
      VGG16+Faster RCNN140159154145148143141153157
      ResNet-101+Faster RCNN172175168169172174176167168
      HOG+MLP(Proposed)810911910898
    • Table 3. Accuracy rate of local area orientation of tower after data augmentation

      View table

      Table 3. Accuracy rate of local area orientation of tower after data augmentation

      AlgorithmFig. 10 (b)Fig. 10 (c)Fig. 10 (d)
      FrontFront sideSideFrontFront sideSideFrontFront sideSide
      ZF-Net+Faster RCNN0.6530.6710.7080.6210.6520.6340.6500.6190.639
      VGG16+Faster RCNN0.7320.7380.7490.6610.7540.7520.7620.7250.778
      ResNet-101+Faster RCNN0.7810.7830.7980.7010.8010.8080.7870.7620.789
      HOG+MLP(Proposed)0.8330.8280.8550.8760.8950.8930.8740.8660.834
    • Table 4. Time required for local area orientation of tower after data augmentationms

      View table

      Table 4. Time required for local area orientation of tower after data augmentationms

      AlgorithmFig. 10 (b)Fig. 10 (c)Fig. 10 (d)
      FrontFront sideSideFrontFront sideSideFrontFront sideSide
      ZF-Net+Faster RCNN313029273233303427
      VGG16+Faster RCNN139148140139148141143142149
      ResNet-101+Faster RCNN168171163165177168179165161
      HOG+MLP(Proposed)10768911998
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    Zuwu Wang, Jun Han, Xiaobin Sun, Bo Yang. Methodfor Orientation Determination of Transmission Line Tower Based on Visual Navigation[J]. Laser & Optoelectronics Progress, 2019, 56(8): 081006

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    Paper Information

    Category: Image Processing

    Received: Oct. 22, 2018

    Accepted: Nov. 13, 2018

    Published Online: Jul. 26, 2019

    The Author Email: Wang Zuwu (wangzuwu@shu.edu.cn)

    DOI:10.3788/LOP56.081006

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