Paper Info
Title
Towards a Behavior Analysis of Remote-Sensed Vessels
Abstract
This paper analyzes the potentialities to classify vessels detected through optical and synthetic-aperture radar (SAR) satellite-borne platforms and estimate their motion. For classification, the discriminative power of a set of geometric features extracted from segmented remote-sensed images is evaluated by clustering data derived from a set of accurate footprints belonging to either tanker or cargo ships. The same procedure is repeated on a few dozens of real, remote-sensed optical images. Concerning velocity estimation, which in this context is based on the detection and analysis of the wake pattern generated by the ship motion, a discussion concerning the accuracy of the wake detection task is presented. In particular, since wake patterns are usually hard to detect, a method is proposed to enhance the wake signal-to-noise ratio, based on a dedicated pre-filtering stage. Results returned by the proposed method are compared with those obtained adopting a standard literature approach, eventually observing that the introduction of the pre-filtering stage improves the wake detection accuracy. A maritime surveillance system based on a pipeline of the modules described here represents a useful tool to support the authorities in charge of monitoring maritime traffic with safety, security and law enforcement purposes.
Year
DOI
Venue
2019
10.1109/SITIS.2019.00100
2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)
Keywords
DocType
ISBN
maritime awareness system,sea surveillance,SAR sensing,optical sensing,image segmentation,image classification,wake detection and analysis
Conference
978-1-7281-5687-3
Citations 
PageRank 
References 
0
0.34
15
Authors
6
Name
Order
Citations
PageRank
M. Reggiannini121.46
Emanuele Salerno225029.21
Massimo Martinelli34710.09
Marco Righi400.34
Marco Tampucci586.66
Luigi Bedini624323.96