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A Clustering Based System for Automated Oil Spill Detection by Satellite Remote Sensing

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Artificial Intelligence and Soft Computing (ICAISC 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9693))

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Abstract

In this work a new software system and environment for detecting objects with specific features within an image is presented. The developed system has been applied to a set of satellite transmitted SAR images, for the purpose of identifying objects like ships with their wake and oil slicks. The systems most interesting characteristic is its flexibility and adaptability to largely different classes of objects and images, which are of interest for several application areas. The heart of the system is represented by the clustering subsystem. This is to extract from the image objects characterized by local properties of small pixel neighborhoods. Among these objects the desired one is sought in later stages by a classifier to be plugged in, chosen from a pool including both soft-computing and conventional ones. An example of application of the system to a recognition problem is presented. The application task is to identify objects like ships with their wake and oil slicks within a set of satellite transmitted SAR images. The reported results have been obtained using a back-propagation neural network.

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Author information

Authors and Affiliations

  1. Department of Electrical Electronics and Informatics Engineering, University of Catania, Viale Andrea Doria 6, 95125, Catania, Italy

    Giacomo Capizzi

  2. Department of Engineering, Roma Tre University, Via Vito Volterra 62, Rome, Italy

    Grazia Lo Sciuto

  3. Institute of Mathematics, Silesian University of Technology, Kaszubska 23, 44-100, Gliwice, Poland

    Marcin Woźniak

  4. Software Engineering Department, Kaunas University of Technology, Studentu 50, Kaunas, Lithuania

    Robertas Damaševicius

Authors
  1. Giacomo Capizzi
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  2. Grazia Lo Sciuto
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  3. Marcin Woźniak
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  4. Robertas Damaševicius
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Corresponding author

Correspondence to Giacomo Capizzi .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Czestochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Czestochowa, Poland

    Marcin Korytkowski

  3. Częstochowa University of Technology, Czestochowa, Poland

    Rafał Scherer

  4. AGH University of Science and Technology, Krakow, Poland

    Ryszard Tadeusiewicz

  5. University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  6. University of Louisville, Louisville, Kentucky, USA

    Jacek M. Zurada

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Capizzi, G., Lo Sciuto, G., Woźniak, M., Damaševicius, R. (2016). A Clustering Based System for Automated Oil Spill Detection by Satellite Remote Sensing. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2016. Lecture Notes in Computer Science(), vol 9693. Springer, Cham. https://doi.org/10.1007/978-3-319-39384-1_54

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  • DOI: https://doi.org/10.1007/978-3-319-39384-1_54

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-39383-4

  • Online ISBN: 978-3-319-39384-1

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