BgCut: Automatic Ship Detection from UAV Images
Joint Authors
Zhang, Dongping
Zhang, Zhengning
Feng, Zhiyong
Xu, Chao
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-04-03
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Ship detection in static UAV aerial images is a fundamental challenge in sea target detection and precise positioning.
In this paper, an improved universal background model based on Grabcut algorithm is proposed to segmentforeground objects from sea automatically.
First, a sea template library including images in different natural conditions is built to provide an initial template to the model.
Then the background trimap is obtained by combing some templates matching with region growing algorithm.
The output trimap initializes Grabcut background instead of manual intervention and the process of segmentation without iteration.
The effectiveness of our proposed model is demonstrated by extensive experiments on a certain area of real UAV aerial images by an airborne Canon 5D Mark.
The proposed algorithm is not only adaptive but also with good segmentation.
Furthermore, the model in this paper can be well applied in the automated processing of industrial images for related researches.
American Psychological Association (APA)
Xu, Chao& Zhang, Dongping& Zhang, Zhengning& Feng, Zhiyong. 2014. BgCut: Automatic Ship Detection from UAV Images. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-1048582
Modern Language Association (MLA)
Xu, Chao…[et al.]. BgCut: Automatic Ship Detection from UAV Images. The Scientific World Journal No. 2014 (2014), pp.1-11.
https://search.emarefa.net/detail/BIM-1048582
American Medical Association (AMA)
Xu, Chao& Zhang, Dongping& Zhang, Zhengning& Feng, Zhiyong. BgCut: Automatic Ship Detection from UAV Images. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-1048582
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1048582