Ship detection from remote sensing imagery is a crucial application for maritime security which includes among others
traffic surveillance, protection against illegal fisheries, oil discharge control and sea pollution monitoring. In the
framework of a European integrated project GMES-Security/LIMES, we developed an operational ship detection
algorithm using high spatial resolution optical imagery to complement existing regulations, in particular the fishing
control system. The automatic detection model is based on statistical methods, mathematical morphology and other
signal processing techniques such as the wavelet analysis and Radon transform. This paper presents current progress
made on the detection model and describes the prototype designed to classify small targets. The prototype was tested on
panchromatic SPOT 5 imagery taking into account the environmental and fishing context in French Guiana. In terms of
automatic detection of small ship targets, the proposed algorithm performs well. Its advantages are manifold: it is simple
and robust, but most of all, it is efficient and fast, which is a crucial point in performance evaluation of advanced ship
detection strategies.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.