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ROV-based binocular vision system for underwater structure crack detection and width measurement

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Abstract

It is efficient to replace human eyes with underwater vehicles equipped with visual sensors to carry out underwater inspections. However, the inability of monocular vision to provide accurate depth information highlights the importance of binocular vision in underwater target detection and measurement. In this paper, an ROV (Remotely Operated Vehicles) based binocular vision system incorporating a specially designed underwater robot is developed to carry out underwater structure detection in real-time. The system is designed to adapt to long-distance and long-duration underwater missions in various underwater environments. Taking cracks as inspection targets, a crack detection and measurement approach is proposed after the robot’s surface cleaning function is applied. Firstly, an affine transformation model is used to enhance the color-distorted underwater images effectively. Then, the multi-directional gray-level fluctuation analysis is applied to acquire an accurate crack segmented result. Finally, the computed disparity map is combined with the segmentation map to determine the crack width quickly. A group of experiments is performed and the validity and effectiveness of the system and crack measurement algorithm are demonstrated.

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Data availability

Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable requests.

Code availability

Our code will be open source in the future.

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Funding

This research was funded by the National Natural Science Foundation of China, grant number 62001156, and the Jiangsu Provincial Key Research and Development Program, grant number BE2019036.

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Authors and Affiliations

  1. College of Internet of Things Engineering, Hohai University, Changzhou, China

    Yunpeng Ma, Yi Wu, Qingwu Li, Yaqin Zhou & Dabing Yu

  2. The Key Laboratory of Sensor Networks and Environmental Sensing, Hohai University, Changzhou, 213022, China

    Qingwu Li

Authors
  1. Yunpeng Ma
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  2. Yi Wu
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Contributions

Conceptualization, Y.M. and Q.L.; methodology, Y.M.; software, D.Y. and Y.Z.; validation, Y.M. and Y.W.; formal analysis, Y.Z.; investigation, Y.Z.; resources, Q.L.; data curation, Y.Z.; writing—original draft preparation, Y.W.; writing—review and editing, Y.M. and Y.W.; visualization, D.Y. and Y.Z.; supervision, Q.L.; project administration, Q.L.; funding acquisition, Y.M. and Q.L. All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Yi Wu.

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Ma, Y., Wu, Y., Li, Q. et al. ROV-based binocular vision system for underwater structure crack detection and width measurement. Multimed Tools Appl 82, 20899–20923 (2023). https://doi.org/10.1007/s11042-022-14168-1

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