A Novel Ship Detection Method Based on Sea State Analysis from Optical Imagery

Author

Yang Guang ; Lu Qichao ; Gao Feng

Author_Institution

Beijing Key Lab. of Digital Media, Beihang Univ., Beijing, China

fYear

2011

fDate

12-15 Aug. 2011

Firstpage

466

Lastpage

471

Abstract

This paper proposes a novel ship detection method based on analyzing the sea state in optical images. This method is composed of three phases. First, the image is segmented with the improved region splitting and merging method, which divides the sea into separated regions. Then, the sea state of each divided region of sea is analyzed by extracting texture roughness and ripple density of a modified differential box counting (DBC) method. Finally, an appropriate algorithm is applied to detect ships for each region of sea. Experimental results test on 36 real remote sensing images and 133 images obtained from Google earth demonstrate that the method is free of image resolution and has little limitation of sea conditions.

Keywords

feature extraction; image resolution; image segmentation; image texture; merging; object detection; remote sensing; Google earth; image resolution; modified differential box counting method; optical imagery; region merging method; region splitting method; remote sensing image; ripple density; sea state analysis; ship detection method; texture roughness extraction; Accuracy; Image resolution; Image segmentation; Marine vehicles; Optical imaging; Optical sensors; Remote sensing; optical image; sea state analysis; ship detection;

fLanguage

English

Publisher

ieee

Conference_Titel

Image and Graphics (ICIG), 2011 Sixth International Conference on

Conference_Location

Hefei, Anhui

Print_ISBN

978-1-4577-1560-0

Electronic_ISBN

978-0-7695-4541-7

Type

conf

DOI

10.1109/ICIG.2011.19

Filename

6005845