An Integrated Strategy toward the Extraction of Contour and Region of Sonar Images

Author:

Xu HuipuORCID,Lu WenjieORCID,Er Meng Joo

Abstract

In this paper, an integrated underwater sonar image extraction strategy, which combines two improved methods, namely the level set method (LSM) and the Lattice Boltzmann Method (LBM), is proposed. First, sonar images are processed by a clustering method and a connected domain analysis to generate the target minimum rectangle frame. Next, the segmentation task is decomposed into two subtasks, namely a coarse segmentation task to obtain the initial contour and a fine segmentation task after embedding the initial contour. Finally, the improved LSM is used to obtain the target contour, and the coarse contour of the segment is embedded into the LBM to obtain the region segmentation of the target in the sonar images. The main contributions of the paper are as follows: (1) The contours and regions of the sonar images are extracted simultaneously. (2) The original LBM method is enhanced to solve the level set iteration problem. (3) The region segmentation with the original image background is extracted, and a more intuitive region segmentation result than that of directly extracting the contour of the level set is achieved. Experimental results based on four evaluation indices of image segmentation show that our method is effective, accurate, and superior to other existing methods.

Publisher

MDPI AG

Subject

Ocean Engineering,Water Science and Technology,Civil and Structural Engineering

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Filtering level-set model based on saliency and gradient information for sonar image segmentation;International Journal of Machine Learning and Cybernetics;2023-10-15

2. An Automated Level-Set Model Fusing Saliency Information for Sonar Image Segmentation;2023 IEEE 3rd International Conference on Computer Communication and Artificial Intelligence (CCAI);2023-05-26

3. Feature Pyramid U-Net with Attention for Semantic Segmentation of Forward-Looking Sonar Images;Sensors;2022-11-03

4. A GUI-Based Automatic Sonar Image Segmentation System;2021 4th International Conference on Intelligent Autonomous Systems (ICoIAS);2021-05

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