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Near real-time automatic vessel detection on optical satellite images

Mattyus, Gellert (2013) Near real-time automatic vessel detection on optical satellite images. In: ISPRS Hannover Workshop, pp. 233-237. ISPRS Archives. ISPRS Hannover Workshop 2013, 21 May - 24 May 2013, Hannover, Germany.

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Official URL: http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-1-W1/

Abstract

Vessel monitoring and surveillance is important for maritime safety and security, environment protection and border control. Ship monitoring systems based on Synthetic-aperture Radar (SAR) satellite images are operational. On SAR images the ships made of metal with sharp edges appear as bright dots and edges, therefore they can be well distinguished from the water. Since the radar is independent from the sun light and can acquire images also by cloudy weather and rain, it provides a reliable service. Vessel detection from spaceborne optical images (VDSOI) can extend the SAR based systems by providing more frequent revisit times and overcoming some drawbacks of the SAR images (e.g. lower spatial resolution, difficult human interpretation). Optical satellite images (OSI) can have a higher spatial resolution thus enabling the detection of smaller vessels and enhancing the vessel type classification. The human interpretation of an optical image is also easier than as of SAR image. In this paper I present a rapid automatic vessel detection method which uses pattern recognition methods, originally developed in the computer vision field. In the first step I train a binary classifier from image samples of vessels and background. The classifier uses simple features which can be calculated very fast. For the detection the classifier is slided along the image in various directions and scales. The detector has a cascade structure which rejects most of the background in the early stages which leads to faster execution. The detections are grouped together to avoid multiple detections. Finally the position, size(i.e. length and width) and heading of the vessels is extracted from the contours of the vessel. The presented method is parallelized, thus it runs fast (in minutes for 16000x16000 pixels image) on a multicore computer, enabling near real-time applications, e.g. one hour from image acquisition to end user.

Item URL in elib:https://elib.dlr.de/82654/
Document Type:Conference or Workshop Item (Poster)
Title:Near real-time automatic vessel detection on optical satellite images
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Mattyus, GellertGellert.Mattyus (at) dlr.deUNSPECIFIED
Date:21 May 2013
Journal or Publication Title:ISPRS Hannover Workshop
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Page Range:pp. 233-237
Publisher:ISPRS Archives
Status:Published
Keywords:Marine, Monitoring, Artificial-Intelligence, Satellite, Optical, Real-time
Event Title:ISPRS Hannover Workshop 2013
Event Location:Hannover, Germany
Event Type:international Conference
Event Dates:21 May - 24 May 2013
Organizer:ISPRS
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Traffic Management (old)
DLR - Research area:Transport
DLR - Program:V VM - Verkehrsmanagement
DLR - Research theme (Project):V - Projekt VABENE (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Photogrammetry and Image Analysis
Deposited By: Mattyus, Gellert Sandor
Deposited On:05 Jun 2013 08:38
Last Modified:31 Jul 2019 19:41

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