Research on underwater target measurement technology based on sonar image and artificial landmark

被引:0
|
作者
Tang, Zhijie [1 ]
Li, Jianda [1 ]
Wang, Zhanhua [1 ]
Huang, Jingke [1 ]
Li, Yang [1 ]
Wang, Chi [1 ]
机构
[1] Shanghai Univ, Sch Mechatron Engn & Automat, 99 Shangda Rd, Shanghai, Peoples R China
基金
中国国家自然科学基金; 上海市自然科学基金;
关键词
Angle measurement; Artificial landmark; Size measurement; Sonar image;
D O I
10.1007/s11042-023-14822-2
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Sonar imaging is one of the important means of underwater target detection. It can measure underwater targets and draw underwater topographic map. However, the existing methods can not rely on sonar images alone to measure underwater targets. In this paper, an underwater measurement technology based on sonar image is proposed. We combine the third-party reference object, artificial landmark to make up for the defects of sonar image measurement. The proposed method includes angle measurement method and three-dimensional mapping algorithm for size measurement. In the experiment, we combine image processing technology to restore the image contour information to obtain the key points in the sonar image. The experimental results show that the accuracy of this method can reach millimeter level, and the error range is within 5%. This technology realizes the shape correction and precise length measurement of underwater targets.
引用
收藏
页码:29713 / 29732
页数:20
相关论文
共 50 条
  • [21] Research on Brain-Inspired SNN for Underwater Target Classification of Sonar Images
    Liu, Yang
    Tian, Meng
    Cao, Kejing
    Wang, Ruiyi
    Zhao, Wei
    Computer Engineering and Applications, 2023, 59 (10) : 204 - 212
  • [22] Target detection algorithm in side-scan sonar image based on pixel importance measurement
    Bian, Hongyu
    Chen, Yiming
    Zhang, Zhigang
    Jiang, Hongrui
    Shengxue Xuebao/Acta Acustica, 2019, 44 (03): : 353 - 359
  • [23] CSLS-CycleGAN based side-scan sonar sample augmentation method for underwater target image
    Tang Y.
    Wang L.
    Yu D.
    Li H.
    Liu M.
    Zhang W.
    Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics, 2024, 46 (05): : 1514 - 1524
  • [24] Sonar Image Target Detection Based on Deep Learning
    Yu, Shibing
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2022, 2022
  • [25] Research on image monitoring system based on artificial intelligence technology
    Wu Jianjun
    AGRO FOOD INDUSTRY HI-TECH, 2017, 28 (01): : 1816 - 1819
  • [26] Underwater biomimetic sonar target detection model based on Hipposideros Pratti
    Pang, Chunyang
    Wang, Feng
    Liu, Yuxin
    BIOINSPIRATION & BIOMIMETICS, 2025, 20 (03)
  • [27] Review and prospect of Underwater Target Feature Extraction Based on Active Sonar
    Wang, Zhong
    Feng, Wei
    Wang, Xinpeng
    PROCEEDINGS OF THE 2017 7TH INTERNATIONAL CONFERENCE ON MANUFACTURING SCIENCE AND ENGINEERING (ICMSE 2017), 2017, 128 : 34 - 37
  • [28] Research on the Image Enhancement Technology of Underwater Image of Supercavitation Vehicle
    Zhao, Xinhua
    Wang, Yue
    Du, Zeshuai
    Ye, Xiufen
    2019 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION (ICMA), 2019, : 1520 - 1524
  • [29] Research on acoustic imaging identification technology of underwater target
    Shi, Min
    Hai, Wei
    Chen, Qian
    Zhang, Zhao-Rong
    Binggong Xuebao/Acta Armamentarii, 2015, 36 : 144 - 148
  • [30] A Glimpse of Research on Underwater Target Intelligent Detection Technology
    Liu, Yifei
    Zhang, Ning
    Xu, Lei
    Huo, Ruikun
    Lin, Pengfei
    2022 IEEE INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING, BIG DATA AND ALGORITHMS (EEBDA), 2022, : 400 - 404