Towards a Behavior Analysis of Remote-Sensed Vessels
| Autor: | Marco Reggiannini, Marco Tampucci, Massimo Martinelli, Marco Righi, Luigi Bedini, Emanuele Salerno |
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| Rok vydání: | 2019 |
| Předmět: |
010504 meteorology & atmospheric sciences
Image classification Computer science Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Optical sensing Wake detection and analysis 0211 other engineering and technologies Context (language use) 02 engineering and technology Wake 01 natural sciences law.invention Discriminative model law Computer vision Radar Cluster analysis 021101 geological & geomatics engineering 0105 earth and related environmental sciences Maritime awareness system Image segmentation business.industry Sea surveillance Pipeline (software) Artificial intelligence SAR sensing business |
| Zdroj: | SITIS 15th International Conference on Signal-Image Technology & Internet-Based Systems, pp. 595–602, Sorrento, Napoli, Italy, 26-29/11/2019 info:cnr-pdr/source/autori:Reggiannini M.; Salerno E.; Martinelli M.; Righi M.; Tampucci M.; Bedini L./congresso_nome:15th International Conference on Signal-Image Technology & Internet-Based Systems/congresso_luogo:Sorrento, Napoli, Italy/congresso_data:26-29%2F11%2F2019/anno:2019/pagina_da:595/pagina_a:602/intervallo_pagine:595–602 |
| DOI: | 10.1109/sitis.2019.00100 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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