首页|Two-Staged Method for Ice Channel Identification Based on Image Seg-mentation and Corner Point Regression

Two-Staged Method for Ice Channel Identification Based on Image Seg-mentation and Corner Point Regression

扫码查看
原文链接
  • NETL
  • NSTL
  • 万方数据
Identification of the ice channel is the basic technology for developing intelligent ships in ice-covered waters,which is important to ensure the safety and economy of navigation.In the Arctic,merchant ships with low ice class often navigate in channels opened up by icebreakers.Navigation in the ice channel often depends on good maneuverability skills and abundant experience from the captain to a large extent.The ship may get stuck if steered into ice fields off the channel.Under this circumstance,it is very important to study how to identify the boundary lines of ice channels with a reliable method.In this paper,a two-staged ice channel identification method is developed based on image segmentation and corner point regression.The first stage employs the image segmentation method to extract channel regions.In the second stage,an intelligent corner regression network is proposed to extract the channel boundary lines from the channel region.A non-intelligent angle-based filtering and clustering method is proposed and compared with corner point regression network.The training and evaluation of the segmentation method and corner regression network are carried out on the synthetic and real ice channel dataset.The evaluation results show that the accuracy of the method using the corner point regression network in the second stage is achieved as high as 73.33%on the synthetic ice channel dataset and 70.66%on the real ice channel dataset,and the processing speed can reach up to 14.58 frames per second.

ice channelship navigationidentificationimage segmentationcorner point regression

DONG Wen-bo、ZHOU Li、DING Shi-feng、WANG Ai-ming、CAI Jin-yan

展开 >

School of Naval Architecture and Ocean Engineering,Jiangsu University of Science and Technology,Zhenjiang 212003,China

School of Naval Architecture,Ocean and Civil Engineering,Shanghai Jiao Tong University,Shanghai 200240,China

National Key Research and Development ProgramGeneral Projects of the National Natural Science Foundation of ChinaHigh-Tech Ship Research Project of the Ministry of Industry and Information Technology

2022YFE010700052171259[2021]342

2024

10.1007/s13344-024-0026-x

中国海洋工程(英文版)
中国海洋学会

中国海洋工程(英文版)

CSTPCDEI
影响因子：0.338
ISSN：0890-5487
年,卷(期)：2024.38(2)
  • 23