A Fast Calibration Method for Underwater Camera Intrinsic Parameters Based on Refraction Model

CHEN Junfeng; JIA Guotao; LI Xueyan; LI Yantian; WANG Xian

doi:10.11993/j.issn.2096-3920.2025-0064

Article Contents

Article Navigation > Journal of Unmanned Undersea Systems > 2025 > Accepted Manuscript

CHEN Junfeng, JIA Guotao, LI Xueyan, LI Yantian, WANG Xian. A Fast Calibration Method for Underwater Camera Intrinsic Parameters Based on Refraction Model[J]. Journal of Unmanned Undersea Systems. doi: 10.11993/j.issn.2096-3920.2025-0064

Citation:

CHEN Junfeng, JIA Guotao, LI Xueyan, LI Yantian, WANG Xian. A Fast Calibration Method for Underwater Camera Intrinsic Parameters Based on Refraction Model[J]. Journal of Unmanned Undersea Systems. doi: 10.11993/j.issn.2096-3920.2025-0064

Citation:

PDF( 2417 KB)

A Fast Calibration Method for Underwater Camera Intrinsic Parameters Based on Refraction Model

doi: 10.11993/j.issn.2096-3920.2025-0064

1.
Guangzhou Naval Representative Bureau, Kunming 650031, China
2.
The 705 Research Institute, China Shipbuilding Industry Corporation Limited, Kunming 650101, China
3.
Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, China

Received Date: 2025-05-02
Accepted Date: 2025-07-04
Rev Recd Date: 2025-07-02

Available Online: 2025-11-04

Abstract

Abstract

To address the low operational precision caused by inaccurate camera intrinsic parameters in underwater visual tasks, a fast calibration method for underwater cameras is proposed. A single image containing two sets of mutually orthogonal parallel lines is used in the proposed method. By solving the vanishing points of these lines on the image plane, an orthogonal relationship related to the equivalent focal length is established. This enables the intrinsic parameters of the camera to be determined. To address the underwater imaging distortion problem, the distortion coefficients are solved using the second-order radial distortion model with the minimum reprojection error as the optimization objective, thereby achieving the distortion calibration of underwater images and improving the accuracy of intrinsic parameter calibration. Furthermore, the accuracy of the method in restoring images is demonstrated by comparing in-air target images with their equivalent air images of underwater targets. Experimental results indicate that the proposed method is simple to operate, significantly reduces environmental requirements during camera calibration, effectively enhances calibration speed while maintaining a certain level of accuracy, and is suitable for calibration tasks of underwater cameras.
- underwater vision,
- camera calibration,
- camera intrinsic parameters,
- vanishing point,
- refraction model

FullText(HTML)

References(16)

References

[1]	DOLEREIT T, VON LUKAS U F, KUIJPER A. Underwater stereo calibration utilizing virtual object points[C]//OCEANS 2015 - Genova. Genova, Italy: OCEANS, 2015: 1-7
[2]	TELEM G, FILIN S. Photogrammetric modeling of underwater environments[J]. ISPRS Journal of Photogram Metry and Remote Sensing, 2010, 65(5): 433-444. doi: 10.1016/j.isprsjprs.2010.05.004
[3]	杨钊, 景包睿, 张频. 基于发射管的UUV自动回收机械臂动力学研究[J]. 舰船科学技术, 2021, 43(11): 163-168. YANG Z, JING B, ZHANG P. Dynamics of automatic recovery manipulator based on pipeline[J]. Ship Science and Technology, 2021, 43(11): 163-168.
[4]	陈强. 水下无人航行器[M]. 国防工业出版社, 2014.
[5]	朱志鹏, 朱志宇. 一种基于双目视觉的水下导引光源检测和测距方法[J]. 水下无人系统学报, 2021, 29(1): 65-73. ZHU Z, ZHU Z. Method for detecting and ranging an underwater guided light source based on binocular vision[J]. Journal of Unmanned Undersea Systems, 2021, 29(03): 299-307.
[6]	季晓燕. 水下目标定位的若干方案对比研究[J]. 舰船电子工程, 2013, 33(3): 121-123. JI X Y. Comparative study of underwater acoustic localization[J]. Ship Science and Technology, 2013, 33(3): 121-123.
[7]	SUN J, WANG H, ZHU X. A fast underwater calibration method based on vanishing point optimization of two orthogonal parallel lines[J]. Measurement, 2021, 178: 109305. doi: 10.1016/j.measurement.2021.109305
[8]	GRACIAS N, SANTOS-VICTOR J. Underwater video mosaics as visual navigation maps[J]. Computer Vision and Image Understanding, 2000, 79(1): 66-91. doi: 10.1006/cviu.2000.0848
[9]	KUNZ C, SINGH H. Stereo self-calibration for seafloor mapping using AUVs[C]//2010 IEEE/OES Autonomous Underwater Vehicles. Monterey, CA, USA: IEEE, 2010: 1-7.
[10]	MELINE A, TRIBOULET J, JOUVENCEL B. A camcorder for 3D underwater reconstruction of archeological objects[C]//OCEANS 2010 MTS/IEEE SEATTLE. Seattle, WA, USA: OCEANS, 2010: 1-9.
[11]	CHEN X, YANG Y H. Two-view camera housing parameters calibration for multi-layer flat refractive interface[C]//2014 IEEE Conference on Computer Vision and Pattern Recognition. Columbus, OH, USA: IEEE, 2014: 524-531
[12]	SHORTIS M. Calibration techniques for accurate measurements by underwater camera systems[J]. Sensors, 2015, 15(12): 30810-30826. doi: 10.3390/s151229831
[13]	YU J, CHEN X, KONG S. Visual Perception and Control of Underwater Robots[M]. CRC Press, 2021.
[14]	董政绩. 基于折射成像模型的水下相机标定与三维重建算法研究[D]. 成都: 电子科技大学, 2024.
[15]	KONOVALENKO I A, SIDORCHUK D S, ZENKIN G M. Analysis and compensation of geometric distortions, appearing when observing objects under water[J]. Pattern Recognition and Image Analysis, 2018, 28: 379-392. doi: 10.1134/S1054661818030112
[16]	ZHANG Z. Flexible camera calibration by viewing a plane from unknown orientations[C]//Proceedings of the Seventh IEEE International Conference on Computer Vision. Kerkyra, Greece: IEEE, 1999: 666-673