A mathematical morphology-based detector for underwater target detection using side-scan sonar images

Jue Hou; Jian Yang

doi:10.1117/12.3029651

21 June 2024 A mathematical morphology-based detector for underwater target detection using side-scan sonar images

Jue Hou, Jian Yang

Proceedings Volume 13167, International Conference on Remote Sensing, Mapping, and Image Processing (RSMIP 2024); 131670D (2024) https://doi.org/10.1117/12.3029651
Event: International Conference on Remote Sensing, Mapping and Image Processing (RSMIP 2024), 2024, Xiamen, China

Abstract

Underwater target detection holds significant importance in domains such as marine exploration, underwater resource management, and marine scientific research. However, due to the complexity of aquatic environments and the presence of noise interference, achieving accurate detection and recognition of underwater targets has remained a challenging task. This paper presents an algorithm grounded in mathematical morphology theory for preprocessing and feature extraction of side-scan sonar images, aimed at underwater target detection and recognition. The algorithm employs operations such as erosion, dilation, opening, and closing, which are fundamental in morphological operations. These operations enhance target outlines, edges, and spatial connectivity within the images, thereby highlighting the shape characteristics of underwater targets. Subsequently, appropriate thresholding and connected component analysis are utilized to accomplish target segmentation and localization. To validate the efficacy of the proposed algorithm, experiments were conducted on a public dataset of side-scan sonar images. Experimental results demonstrate the feasibility of the introduced mathematical morphology-based algorithm in underwater side-scan sonar target detection. In comparison with methods based on deep learning, the proposed algorithm exhibits comparable detection performance with a notable efficiency advantage under constrained computational resources.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jue Hou and Jian Yang "A mathematical morphology-based detector for underwater target detection using side-scan sonar images", Proc. SPIE 13167, International Conference on Remote Sensing, Mapping, and Image Processing (RSMIP 2024), 131670D (21 June 2024); https://doi.org/10.1117/12.3029651

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KEYWORDS

Image processing

Target detection

Detection and tracking algorithms

Image segmentation

Mathematical morphology

Image processing algorithms and systems

Submerged target detection

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