An integrated ship segmentation method based on discriminator and extractor

doi:10.1016/j.imavis.2019.11.002

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 智能机器人系统研究

	An integrated ship segmentation method based on discriminator and extractor
	Zhang, Wen 1; He, Xujie 1; Li, Wanyi2 ; Zhang, Zhi 1; Luo, Yongkang2 ; Su, Li 1; Wang, Peng2
发表期刊	IMAGE AND VISION COMPUTING
ISSN	0262-8856
	2020
卷号	93 页码:12
通讯作者	He, Xujie(hexujie@hrbeu.edu.cn)
摘要	Ship segmentation is an important task in maritime surveillance systems. A great deal of research on image segmentation has been done in the past few years, but there appears to be some problems when directly utilizing them for ship segmentation under complex maritime background. The interference factors decreasing segmentation performance usually are from the peculiarity of complex maritime background, such as the existence of sea fog, large wakes and large waves. To deal with these interference factors, this paper presents an integrated ship segmentation method based on discriminator and extractor (ISDE). Different from traditional segmentation methods, our method consists of two components in light of the structure: Interference Factor Discriminator (IFD) and Ship Extractor (SE). SqueezeNet is employed for the implementation of IFD as the first step to make a judgment on what interference factors are contained in the input image. While DeepLabv3 + and improved DeepLabv3 + are employed for the implementation of SE as the second step to finally extract ships. We collect a ship segmentation dataset and conduct intensive experiments on it. The experimental results demonstrate that our method for ship segmentation outperforms state-of-the-art methods in terms of segmentation accuracy, especially for the images contain sea fog. Besides our method can run in real time as well. (C) 2019 Elsevier B.V. All rights reserved.
关键词	Ship segmentation Sea fog Classification Interference Factor Discriminator Ship extractor
DOI	10.1016/j.imavis.2019.11.002
关键词[WOS]	RECONSTRUCTION
收录类别	SCI
语种	英语
资助项目	National Key R&D Program Projects[2018YEB1601502] ; National Key R&D Program Projects[2018YEB1601502]
项目资助者	National Key R&D Program Projects
WOS研究方向	Computer Science ; Engineering ; Optics
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Software Engineering ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic ; Optics
WOS记录号	WOS:000514016000011
出版者	ELSEVIER
引用统计	被引频次：21[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/38421
专题	多模态人工智能系统全国重点实验室_智能机器人系统研究
通讯作者	He, Xujie
作者单位	1.Harbin Engn Univ China, Coll Automat, Harbin 150001, Peoples R China 2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Wen,He, Xujie,Li, Wanyi,et al. An integrated ship segmentation method based on discriminator and extractor[J]. IMAGE AND VISION COMPUTING,2020,93:12.
APA	Zhang, Wen.,He, Xujie.,Li, Wanyi.,Zhang, Zhi.,Luo, Yongkang.,...&Wang, Peng.(2020).An integrated ship segmentation method based on discriminator and extractor.IMAGE AND VISION COMPUTING,93,12.
MLA	Zhang, Wen,et al."An integrated ship segmentation method based on discriminator and extractor".IMAGE AND VISION COMPUTING 93(2020):12.