Wreckage Target Recognition in Side-scan Sonar Images Based on an Improved Faster R-CNN Model

Author(s):  
Tang Yulin ◽  
Jin Shaohua ◽  
Bian Gang ◽  
Zhang Yonzhou ◽  
Li Fan
2021 ◽  
Vol 13 (18) ◽  
pp. 3555
Author(s):  
Yongcan Yu ◽  
Jianhu Zhao ◽  
Quanhua Gong ◽  
Chao Huang ◽  
Gen Zheng ◽  
...  

To overcome the shortcomings of the traditional manual detection of underwater targets in side-scan sonar (SSS) images, a real-time automatic target recognition (ATR) method is proposed in this paper. This method consists of image preprocessing, sampling, ATR by integration of the transformer module and YOLOv5s (that is, TR–YOLOv5s), and target localization. By considering the target-sparse and feature-barren characteristics of SSS images, a novel TR–YOLOv5s network and a down-sampling principle are put forward, and the attention mechanism is introduced in the method to meet the requirements of accuracy and efficiency for underwater target recognition. Experiments verified the proposed method achieved 85.6% mean average precision (mAP) and 87.8% macro-F2 score, and brought 12.5% and 10.6% gains compared with the YOLOv5s network trained from scratch, and had the real-time recognition speed of about 0.068 s per image.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 173450-173460
Author(s):  
Tang Yulin ◽  
Shaohua Jin ◽  
Gang Bian ◽  
Yonghou Zhang

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 29416-29428
Author(s):  
Xiaoming Qin ◽  
Xiaowen Luo ◽  
Ziyin Wu ◽  
Jihong Shang

1992 ◽  
Vol 14 (2) ◽  
pp. 125-136 ◽  
Author(s):  
D. C. Mason ◽  
T. P. LeBas ◽  
I. Sewell ◽  
C. Angelikaki
Keyword(s):  

2019 ◽  
Vol 11 (11) ◽  
pp. 1281 ◽  
Author(s):  
Xiufen Ye ◽  
Haibo Yang ◽  
Chuanlong Li ◽  
Yunpeng Jia ◽  
Peng Li

When side-scan sonars collect data, sonar energy attenuation, the residual of time varying gain, beam patterns, angular responses, and sonar altitude variations occur, which lead to an uneven gray level in side-scan sonar images. Therefore, gray scale correction is needed before further processing of side-scan sonar images. In this paper, we introduce the causes of gray distortion in side-scan sonar images and the commonly used optical and side-scan sonar gray scale correction methods. As existing methods cannot effectively correct distortion, we propose a simple, yet effective gray scale correction method for side-scan sonar images based on Retinex given the characteristics of side-scan sonar images. Firstly, we smooth the original image and add a constant as an illumination map. Then, we divide the original image by the illumination map to produce the reflection map. Finally, we perform element-wise multiplication between the reflection map and a constant coefficient to produce the final enhanced image. Two different schemes are used to implement our algorithm. For gray scale correction of side-scan sonar images, the proposed method is more effective than the latest similar methods based on the Retinex theory, and the proposed method is faster. Experiments prove the validity of the proposed method.


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