S<sup>3</sup>DR-Det: A Rotating Target Detection Model for High Aspect Ratio Shipwreck Targets in Side-Scan Sonar Images
The characteristics of multi-directional rotation and high aspect ratio of targets such as shipwrecks lead to low detection accuracy and difficulty localizing existing detection models for this target type. Through our research, we design three main inconsistencies in rotating target detection compa...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/17/2/312 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832587568878714880 |
|---|---|
| author | Quanhong Ma Shaohua Jin Gang Bian Yang Cui Guoqing Liu Yihan Wang |
| author_facet | Quanhong Ma Shaohua Jin Gang Bian Yang Cui Guoqing Liu Yihan Wang |
| author_sort | Quanhong Ma |
| collection | DOAJ |
| description | The characteristics of multi-directional rotation and high aspect ratio of targets such as shipwrecks lead to low detection accuracy and difficulty localizing existing detection models for this target type. Through our research, we design three main inconsistencies in rotating target detection compared to traditional target detection, i.e., inconsistency between target and anchor frame, inconsistency between classification features and regression features, and inconsistency between rotating frame quality and label assignment strategy. In this paper, to address the discrepancies in the above three aspects, we propose the Side-scan Sonar Dynamic Rotating Target Detector (S<sup>3</sup>DR-Det), which is a model with a dynamic rotational convolution (DRC) module designed to effectively gather rotating targets’ high-quality features during the model’s feature extraction phase, a feature decoupling module (FDM) designed to distinguish between the various features needed for regression and classification in the detection phase, and a dynamic label assignment strategy based on spatial matching prior information (S-A) specific to rotating targets in the training phase, which can more reasonably and accurately classify positive and negative samples. The three modules not only solve the problems unique to each stage but are also highly coupled to solve the difficulties of target detection caused by the multi-direction and high aspect ratio of the target in the side-scan sonar image. Our model achieves an average accuracy (AP) of 89.68% on the SSUTD dataset and 90.19% on the DNASI dataset. These results indicate that our model has excellent detection performance. |
| format | Article |
| id | doaj-art-53f20c7622a746e4b869d68c93afe73d |
| institution | Kabale University |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-53f20c7622a746e4b869d68c93afe73d2025-01-24T13:48:05ZengMDPI AGRemote Sensing2072-42922025-01-0117231210.3390/rs17020312S<sup>3</sup>DR-Det: A Rotating Target Detection Model for High Aspect Ratio Shipwreck Targets in Side-Scan Sonar ImagesQuanhong Ma0Shaohua Jin1Gang Bian2Yang Cui3Guoqing Liu4Yihan Wang5Department of Oceanography and Hydrography, Dalian Naval Academy, Dalian 116018, ChinaDepartment of Oceanography and Hydrography, Dalian Naval Academy, Dalian 116018, ChinaDepartment of Oceanography and Hydrography, Dalian Naval Academy, Dalian 116018, ChinaDepartment of Oceanography and Hydrography, Dalian Naval Academy, Dalian 116018, ChinaDepartment of Oceanography and Hydrography, Dalian Naval Academy, Dalian 116018, ChinaDepartment of Oceanography and Hydrography, Dalian Naval Academy, Dalian 116018, ChinaThe characteristics of multi-directional rotation and high aspect ratio of targets such as shipwrecks lead to low detection accuracy and difficulty localizing existing detection models for this target type. Through our research, we design three main inconsistencies in rotating target detection compared to traditional target detection, i.e., inconsistency between target and anchor frame, inconsistency between classification features and regression features, and inconsistency between rotating frame quality and label assignment strategy. In this paper, to address the discrepancies in the above three aspects, we propose the Side-scan Sonar Dynamic Rotating Target Detector (S<sup>3</sup>DR-Det), which is a model with a dynamic rotational convolution (DRC) module designed to effectively gather rotating targets’ high-quality features during the model’s feature extraction phase, a feature decoupling module (FDM) designed to distinguish between the various features needed for regression and classification in the detection phase, and a dynamic label assignment strategy based on spatial matching prior information (S-A) specific to rotating targets in the training phase, which can more reasonably and accurately classify positive and negative samples. The three modules not only solve the problems unique to each stage but are also highly coupled to solve the difficulties of target detection caused by the multi-direction and high aspect ratio of the target in the side-scan sonar image. Our model achieves an average accuracy (AP) of 89.68% on the SSUTD dataset and 90.19% on the DNASI dataset. These results indicate that our model has excellent detection performance.https://www.mdpi.com/2072-4292/17/2/312side-scan sonarshipwreck targetsrotating target detectionlabel assignment strategy |
| spellingShingle | Quanhong Ma Shaohua Jin Gang Bian Yang Cui Guoqing Liu Yihan Wang S<sup>3</sup>DR-Det: A Rotating Target Detection Model for High Aspect Ratio Shipwreck Targets in Side-Scan Sonar Images Remote Sensing side-scan sonar shipwreck targets rotating target detection label assignment strategy |
| title | S<sup>3</sup>DR-Det: A Rotating Target Detection Model for High Aspect Ratio Shipwreck Targets in Side-Scan Sonar Images |
| title_full | S<sup>3</sup>DR-Det: A Rotating Target Detection Model for High Aspect Ratio Shipwreck Targets in Side-Scan Sonar Images |
| title_fullStr | S<sup>3</sup>DR-Det: A Rotating Target Detection Model for High Aspect Ratio Shipwreck Targets in Side-Scan Sonar Images |
| title_full_unstemmed | S<sup>3</sup>DR-Det: A Rotating Target Detection Model for High Aspect Ratio Shipwreck Targets in Side-Scan Sonar Images |
| title_short | S<sup>3</sup>DR-Det: A Rotating Target Detection Model for High Aspect Ratio Shipwreck Targets in Side-Scan Sonar Images |
| title_sort | s sup 3 sup dr det a rotating target detection model for high aspect ratio shipwreck targets in side scan sonar images |
| topic | side-scan sonar shipwreck targets rotating target detection label assignment strategy |
| url | https://www.mdpi.com/2072-4292/17/2/312 |
| work_keys_str_mv | AT quanhongma ssup3supdrdetarotatingtargetdetectionmodelforhighaspectratioshipwrecktargetsinsidescansonarimages AT shaohuajin ssup3supdrdetarotatingtargetdetectionmodelforhighaspectratioshipwrecktargetsinsidescansonarimages AT gangbian ssup3supdrdetarotatingtargetdetectionmodelforhighaspectratioshipwrecktargetsinsidescansonarimages AT yangcui ssup3supdrdetarotatingtargetdetectionmodelforhighaspectratioshipwrecktargetsinsidescansonarimages AT guoqingliu ssup3supdrdetarotatingtargetdetectionmodelforhighaspectratioshipwrecktargetsinsidescansonarimages AT yihanwang ssup3supdrdetarotatingtargetdetectionmodelforhighaspectratioshipwrecktargetsinsidescansonarimages |