Underwater sonar image detection algorithm based on corner

GuoLiang Yang; Huang Cong; Ming Zhao; ZhiPeng Gong

doi:10.1117/12.2641395

10 November 2022 Underwater sonar image detection algorithm based on corner

GuoLiang Yang, Huang Cong, Ming Zhao, ZhiPeng Gong

Proceedings Volume 12348, 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022); 123481B (2022) https://doi.org/10.1117/12.2641395
Event: 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022), 2022, Zhuhai, China

Abstract

Aiming at the problems of large target size difference, blurred imaging and serious occlusion in sonar image, a target detection method based on corner is proposed. On the basis of CornerNet, an adaptive corner feature matching module is added to automatically select the features suitable for the target size and give them high weight, so as to realize the dynamic multi feature map hierarchical prediction and improve the quality of predicted corners; The prediction of embedded vector is cancelled, and a new layer structure is used to replace the embedded layer to realize corner grouping and reduce the false detection rate of the model. The experimental results show that the improved CornerNet has higher recall and better detection accuracy than other sonar image target detection algorithms.

Citation Download Citation

GuoLiang Yang, Huang Cong, Ming Zhao, and ZhiPeng Gong "Underwater sonar image detection algorithm based on corner", Proc. SPIE 12348, 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022), 123481B (10 November 2022); https://doi.org/10.1117/12.2641395

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KEYWORDS

Detection and tracking algorithms

Target detection

Image enhancement

Image processing

Binary data

Data modeling

Feature extraction

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