Processing satellite imagery to detect and identify non-collaborative vessels

Reggiannini M., Righi M.

Image analysis  Computer vision  Earth Satellites  Dynamic Scene Analysis  Feature extraction  Image classification  Machine learning  Maritime surveillance  Remote sensing  Synthetic aperture radar imagery 

In recent years, European maritime countries have had to deal with new situations involving the traffic of illegal vessels. In order to tackle such problems, systems are required that can detect relevant anomalies such as unauthorised fishing or irregular migration and related smuggling activity. The OSIRIS project aims to contribute to a solution to these problems with the use of large scale data provided by satellite missions (Sentinel, Cosmo-SkyMed, EROS). Optical/SAR data and system Integration for Rush Identification of Ship models (OSIRIS) is a European Space Agency project launched in March 2016, with the primary purpose of developing a software platform dedicated to maritime surveillance. The platform will be in charge of: (i) collecting maritime remote sensing data provided by satellite missions such as Sentinel-1, Sentinel-2, Cosmo-SkyMed and EROS-B, and (ii) processing the acquired data in order to detect and classify seagoing vessels. A main goal within OSIRIS is to develop computational imaging procedures to process Synthetic Aperture Radar and Optical data returned by satellite sensors. We propose a system to automatically detect and recognise all the vessels within in a given area; the maritime satellite imagery will be processed to extract visual informative features of candidate vessels and to assign an identification label to each vessel.

Source: ERCIM news (2017): 25–26.

Publisher: ERCIM., Le Chesnay