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Drift Ice Detection Using a Self-organizing Neural Network

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3681))

Abstract

This paper proposes a segmentation method of SAR (Synthetic Aperture Radar) images based on a SOM (Self-Organizing Map) neural network. SAR images are obtained by observation using microwave sensor. For teacher data generation, they are segmented into the drift ice (thick and thin), and sea regions manually, and then their features are extracted from partitioned data. However they are not necessarily effective for neural network learning because they might include incorrectly segmented data. Therefore, in particular, a multi-step SOM is used as a learning method to improve reliability of teacher data, and carry out classification. This process enable us to fix all mistook data and segment the SAR image data using just data. The validity of this method was demonstrated by means of computer simulations using the actual SAR images.

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References

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Author information

Authors and Affiliations

  1. Dept. of Information Science and Intelligent Systems, University of Tokushima, 2-1, Minami-Josanjima, 770-8506, Japan

    Minoru Fukumi & Taketsugu Nagao

  2. Faculty of Education, Okayama University, 3-1-1, Tsushima-Naka, Okayama, 700-8530, Japan

    Yasue Mitsukura

  3. La Trobe University, Melbourne, Australia

    Rajiv Khosla

Authors
  1. Minoru Fukumi
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  2. Taketsugu Nagao
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  3. Yasue Mitsukura
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  4. Rajiv Khosla
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Editor information

Editors and Affiliations

  1. School of Business, La Trobe University, 3086, Melbourne, Victoria, Australia

    Rajiv Khosla

  2. Centre for SMART systems Engineering Research Centre, University of Brighton, Moulsecoomb, BN2 4GJ, Brighton, UK

    Robert J. Howlett

  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, 5095, Mawson Lakes, SA, Australia

    Lakhmi C. Jain

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© 2005 Springer-Verlag Berlin Heidelberg

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Fukumi, M., Nagao, T., Mitsukura, Y., Khosla, R. (2005). Drift Ice Detection Using a Self-organizing Neural Network. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552413_181

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  • DOI: https://doi.org/10.1007/11552413_181

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28894-7

  • Online ISBN: 978-3-540-31983-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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