Laser & Optoelectronics Progress, Volume. 58, Issue 4, 0410011(2021)

Photogrammetric Coded Point Localization Based on Target Detection Network

Dahui Qin, Dong Cheng*, Mingzhu Su, Yunfei Duan, and Yongbo Shao
Author Affiliations
  • School of Civil Engineering and Geomatics, Southwest Petroleum University, Chengdu, Sichuan 610500, China
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    In order to solve the problem that traditional photogrammetric coded point location depends on multiple relationship criteria, complex judgment, and unstable recognition, a localization method is proposed, which uses the target detection network based on improved YOLO v3 to segment the coding points, and uses distance sorting to identify the center mark points. First, the feature extraction network is improved according to the characteristics of the coded mark points, and the coded points are quickly identified from the complex background. Then, image processing is carried out in the prediction frame to calculate the distance from the centroid of the contour to the center, and then the circular mark points of the positioning center are sorted. Finally, the scale coding point data set is constructed for network training and testing. The experimental results show that the recognition accuracy of the target detection network for coded points reaches 94.91%, which is less affected by the environment and noise, and the distance criterion has high accuracy. The location method has the advantages of good adaptability and high robustness.

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    Dahui Qin, Dong Cheng, Mingzhu Su, Yunfei Duan, Yongbo Shao. Photogrammetric Coded Point Localization Based on Target Detection Network[J]. Laser & Optoelectronics Progress, 2021, 58(4): 0410011

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    Paper Information

    Category: Image Processing

    Received: Jun. 28, 2020

    Accepted: Aug. 7, 2020

    Published Online: Feb. 8, 2021

    The Author Email: Cheng Dong (chengdong203@qq.com)

    DOI:10.3788/LOP202158.0410011

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