DocumentCode
9997
Title
A New Method on Inshore Ship Detection in High-Resolution Satellite Images Using Shape and Context Information
Author
Ge Liu ; Yasen Zhang ; Xinwei Zheng ; Xian Sun ; Kun Fu ; Hongqi Wang
Author_Institution
Key Lab. of Technol. in Geospatial Inf. Process. & Applic. Syst., Inst. of Electron., Beijing, China
Volume
11
Issue
3
fYear
2014
fDate
Mar-14
Firstpage
617
Lastpage
621
Abstract
In this letter, we present a new method to detect inshore ships using shape and context information. We first propose a new energy function based on an active contour model to segment water and land and minimize it with an iterative global optimization method. The proposed energy performs well on the different intensity distributions between water and land and produces a result that can be well used in shape and context analyses. In the segmented image, ships are detected with successive shape analysis, including shape analysis in the localization of ship head and region growing in computing the width and length of ship. Finally, to locate ships accurately and remove the false alarms, we unify them with a binary linear programming problem by utilizing the context information. Experiments on QuickBird images show the robustness and precision of our method.
Keywords
image segmentation; iterative methods; object detection; optimisation; remote sensing; shape recognition; ships; active contour model; context information; energy function; high resolution satellite image; image segmentation; inshore ship detection; iterative global optimization method; land segmentation; shape information; water segmentation; Algorithm design and analysis; Context; Head; Image segmentation; Linear programming; Marine vehicles; Shape; Active contour model; binary linear programming; context information; inshore ship detection; shape analysis;
fLanguage
English
Journal_Title
Geoscience and Remote Sensing Letters, IEEE
Publisher
ieee
ISSN
1545-598X
Type
jour
DOI
10.1109/LGRS.2013.2272492
Filename
6600859
Link To Document