Oil spill identification in X-band marine radar image using K-means and texture feature

Author:

Chen Rong1,Li Bo1,Jia Baozhu12,Xu Jin1,Ma Long1,Yang Hongbo1,Wang Haixia3

Affiliation:

1. Naval Architecture and Shipping College, Guangdong Ocean University, Zhanjiang, Guangdong, China

2. Technical Research Center for Ship Intelligence and Safety Engineering of Guangdong Province, Guangdong, China

3. Navigation College, Dalian Martime University, Dalian, Liaoning, China

Abstract

Marine oil pollution poses a serious threat to the marine ecological balance. It is of great significance to develop rapid and efficient oil spill detection methods for the mitigation of marine oil spill pollution and the restoration of the marine ecological environment. X-band marine radar is one of the important monitoring devices, in this article, we perform the digital X-band radar image by “Sperry Marine” radar system for an oil film extraction experiment. First, the de-noised image was obtained by preprocessing the original image in the Cartesian coordinate system. Second, it was cut into slices. Third, the texture features of the slices were calculated based on the gray-level co-occurrence matrix (GLCM) and K-means method to extract the rough oil spill regions. Finally, the oil spill regions were segmented using the Sauvola threshold algorithm. The experimental results indicate that this study provides a scientific method for the research of oil film extraction. Compared with other methods of oil spill extraction in X-band single-polarization marine radar images, the proposed technology is more intelligent, and it can provide technical support for marine oil spill emergency response in the future.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Guangdong Province

Research start-up funding project of Guangdong Ocean University

Universitiy Special projects of Guangdong Province

Publisher

PeerJ

Subject

General Computer Science

Reference46 articles.

1. Observation of oil slicks on the sea surface by using marine navigation radar;Atanassov,2002

2. 3D texture feature extraction and classification using GLCM and LBP-based descriptors;Barburiceanu;Applied Sciences,2021

3. Robust Satellite Techniques for oil spill detection and monitoring using AVHRR thermal infrared bands;Casciello;International Journal of Remote Sensing,2011

4. On the use of simulated airborne compact polarimetric SAR for characterizing oil–water mixing of the deepwater horizon oil spill;Collins;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2015

5. Google earth and Google fusion tables in support of time-critical collaboration: mapping the deepwater horizon oil spill with the AVIRIS airborne spectrometer;Eliza;Earth Science Informatics,2011

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3