Title :
Interactive ship segmentation in SAR images
Author :
Akyilmaz, E. ; Demirkesen, Can ; Nar, F. ; Okman, E. ; Cetin, Mujdat
Author_Institution :
Uzay ve Savunma Teknolojileri (SDT), ODTU Teknokent, Ankara, Turkey
Abstract :
Ship detection from synthetic aperture radar (SAR) images is important for various automatic target recognition (ATR) tasks. Although the ships in offshore areas can be easily detected, the ones near the shores or close to each other are difficult to detect. Furthermore, segmentation and classification of such ships is extremely difficult. In this study, a novel approach is presented for the fast and accurate segmentation of ship boundaries with minimal user interaction. In this approach, the rough location and orientation of a ship is determined by the user. Then, a ship model, which is constructed from synthetic ship images, is fitted on to the ship selected by the user and accurate ship boundaries are extracted. The effectiveness of the proposed algorithm is demonstrated by experimental results.
Keywords :
image classification; image segmentation; object detection; radar imaging; ships; synthetic aperture radar; ATR; SAR images; automatic target recognition; image classification; image segmentation; interactive ship segmentation; rough location; synthetic aperture radar images; synthetic ship images; Active shape model; Image segmentation; Marine vehicles; Radar imaging; Support vector machines; Synthetic aperture radar; SAR; ship detection; ship segmentation;
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2013 21st
Conference_Location :
Haspolat
Print_ISBN :
978-1-4673-5562-9
Electronic_ISBN :
978-1-4673-5561-2
DOI :
10.1109/SIU.2013.6531526