Open Access

ARTICLE

Fast Segmentation Method of Sonar Images for Jacket Installation Environment

Hande Mao^1,2, Hongzhe Yan¹, Lei Lin¹, Wentao Dong^1,3, Yuhang Li¹, Yuliang Liu^2,4,*, Jing Xue⁵

1 COOEC-Fluor Heavy Industries Co., Ltd., Zhuhai, 519000, China
2 Zhejiang Ocean University, Zhoushan, 316022, China
3 Saint Petersburg State Marine Technical University, Saint Petersburg, 190000, Russia
4 Wenzhou Institute of Technology, Wenzhou, 325035, China
5 Deakin University, Burwood, VIC 3125, 430070, Australia

* Corresponding Author: Yuliang Liu. Email:

Intelligent Automation & Soft Computing 2023, 36(2), 1671-1686. https://doi.org/10.32604/iasc.2023.028819

Received 18 February 2022; Accepted 05 May 2022; Issue published 05 January 2023

Abstract

It has remained a hard nut for years to segment sonar images of jacket installation environment, most of which are noisy images with inevitable blur after noise reduction. For the purpose of solutions to this problem, a fast segmentation algorithm is proposed on the basis of the gray value characteristics of sonar images. This algorithm is endowed with the advantage in no need of segmentation thresholds. To realize this goal, we follow the undermentioned steps: first, calculate the gray matrix of the fuzzy image background. After adjusting the gray value, the image is divided into three regions: background region, buffer region and target regions. After filtering, we reset the pixels with gray value lower than 255 to binarize images and eliminate most artifacts. Finally, the remaining noise is removed by morphological processing. The simulation results of several sonar images show that the algorithm can segment the fuzzy sonar images quickly and effectively. Thus, the stable and feasible method is testified.

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Keywords

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