TY - GEN
T1 - Research on Ship Wake Detection Method Based on Composite Mode
AU - Xing, Hao
AU - Wang, Yankai
AU - Han, Jipeng
AU - Bai, Jiaqi
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Ship wake is an important military target, while the ocean background data in satellite images is huge, and ship wake targets are few. How to quickly and accurately find targets in large amounts of data is a valuable research topic. The ship wake target has a different detection method from the general target, as it has the characteristics of uniform background and prominent line characteristics. In this paper, we design a ship wake detection method which can quickly screen out easily detected samples by using traditional algorithms including Gaussian filtering, Canny edge detection and probabilistic Hough transform. We used typical representative YOLOv5 and Faster-R-CNN target detection frameworks to train single-stage and two-stage target detection models. In the process of integrating traditional algorithms into ship wake detection, we have built a ship wake target detection system that combines traditional algorithms with neural network methods. The experiment shows that the improved traditional wake detection algorithm can effectively improve the efficiency of ship wake detection system in target detection task.
AB - Ship wake is an important military target, while the ocean background data in satellite images is huge, and ship wake targets are few. How to quickly and accurately find targets in large amounts of data is a valuable research topic. The ship wake target has a different detection method from the general target, as it has the characteristics of uniform background and prominent line characteristics. In this paper, we design a ship wake detection method which can quickly screen out easily detected samples by using traditional algorithms including Gaussian filtering, Canny edge detection and probabilistic Hough transform. We used typical representative YOLOv5 and Faster-R-CNN target detection frameworks to train single-stage and two-stage target detection models. In the process of integrating traditional algorithms into ship wake detection, we have built a ship wake target detection system that combines traditional algorithms with neural network methods. The experiment shows that the improved traditional wake detection algorithm can effectively improve the efficiency of ship wake detection system in target detection task.
KW - Canny edge detection
KW - deep learning
KW - neural network
KW - probabilistic Hough transform
KW - ship wake detection
UR - http://www.scopus.com/inward/record.url?scp=85152430142&partnerID=8YFLogxK
U2 - 10.1109/ICCRD56364.2023.10080122
DO - 10.1109/ICCRD56364.2023.10080122
M3 - Conference contribution
AN - SCOPUS:85152430142
T3 - 2023 15th International Conference on Computer Research and Development, ICCRD 2023
SP - 290
EP - 297
BT - 2023 15th International Conference on Computer Research and Development, ICCRD 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th International Conference on Computer Research and Development, ICCRD 2023
Y2 - 10 January 2023 through 12 January 2023
ER -