Affiliation:
1. College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, China
Abstract
There are many challenges in using side-scan sonar (SSS) images to detect objects. The challenge of object detection and recognition in sonar data is greater than in optical images due to the sparsity of detectable targets. The complexity of real-world underwater scanning presents additional difficulties, as different angles produce sonar images of varying characteristics. This heterogeneity makes it difficult for algorithms to accurately identify and detect sonar objects. To solve these problems, this paper presents a novel method for sonar image target detection based on a transformer and YOLOv7. Thus, two data augmentation techniques are introduced to improve the performance of the detection system. The first technique applies stain-like noise to the training optical image data to simulate the real sonar image environment. The second technique adds multiple shadows to the optical image and 3D data targets to represent the direction of the target in the sonar image. The proposed method is evaluated on a public sonar image dataset, and the experimental results demonstrate that the proposed method outperforms the state-of-the-art methods in terms of accuracy and speed. The experimental results show that our method achieves better precision.
Funder
National Natural Science Foundation of China
Fundamental Research Funds for the Central Universities
Reference41 articles.
1. Advancements in the field of autonomous underwater vehicle;Sahoo;Ocean Eng.,2019
2. Wang, J., Li, H., Huo, G., Li, C., and Wei, Y. (2023). Multi-Modal Multi-Stage Underwater Side-Scan Sonar Target Recognition Based on Synthetic Images. Remote Sens., 15.
3. Er, M.J., Chen, J., Zhang, Y., and Gao, W. (2023). Research Challenges, Recent Advances, and Popular Datasets in Deep Learning-Based Underwater Marine Object Detection: A Review. Sensors, 23.
4. Comprehensive sample augmentation by fully considering SSS imaging mechanism and environment for shipwreck detection under zero real samples;Huang;IEEE Trans. Geosci. Remote Sens.,2021
5. Underwater Forward-Looking Sonar Images Target Detection via Speckle Reduction and Scene Prior;Long;IEEE Trans. Geosci. Remote Sens.,2023
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