Abstract
Imaging sonars are widely used in underwater intelligent transportation, underwater intelligent perception, intelligent underwater robot navigation, etc. The image segmentation is often a key step in sonar image processing. There have been many approaches of segmenting sonar images, and each method has its own characteristics. The approaches of segmenting images using the variational methods have attracted widespread attentions from scholars. A segmentation method for sonar images using a variational method is given in this paper, and it is compared with other commonly used methods for the image segmentation. The experimental results indicate that the method given in this paper is able to obtain the target contours and has fewer false contours, and the contours are closed. However, the method requires iterative operations and requires a large amount of calculation and has poor real-time performance.
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Acknowledgements
This work is supported by Hainan Provincial Natural Science Foundation of China (No. 420CXTD439), and the National Science Foundation of China (No. 61661038).
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Tian, Y., Xue, Y., Guo, H. (2021). Sonar Image Segmentation of Seabed Targets Using a Variational Approach. In: Jain, L.C., Kountchev, R., Shi, J. (eds) 3D Imaging Technologies—Multi-dimensional Signal Processing and Deep Learning. Smart Innovation, Systems and Technologies, vol 234. Springer, Singapore. https://doi.org/10.1007/978-981-16-3391-1_14
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DOI: https://doi.org/10.1007/978-981-16-3391-1_14
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