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Estimation of Sea Ice Movement Using Locally Parallel Matching Model

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2003)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2773))

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Abstract

In order to estimate the velocity of sea ice movement, according to the characters of sea ice image, an effect method has been adopted: Proper candidate points are found by using interest operators, a locally parallel model for matching is constructed to analyze the disparity of sequential images, after a certain post processing, the estimation of the velocity could be got by using a orientation choosing and maximum probability decision method. The algorithm has shown good performance in practice for estimating velocity of sea ice in Bohai.

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Author information

Authors and Affiliations

  1. Dept. of Electronic Engineering, Dalian Univ. of Technology, Dalian, 116024, China

    Kong Xiangwei, Chen Feishi, Liu Zhiyuan & Zong Shaoxiang

Authors
  1. Kong Xiangwei
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  2. Chen Feishi
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  3. Liu Zhiyuan
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  4. Zong Shaoxiang
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Editor information

Editors and Affiliations

  1. Computing Laboratory, Oxford University, Parks Road, OXI 3QD, United Kingdom

    Vasile Palade

  2. Intelligent Systems and Signal Processing Labs, Moulsecoomb, University of Brighton, BN2 4GJ, Brighton, United Kingdom

    Robert J. Howlett

  3. Knowledge-Based Intelligent Engineering Systems Centre, Mawson Lakes, University of South Australia, 5095, Adelaide, SA, Australia

    Lakhmi Jain

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© 2003 Springer-Verlag Berlin Heidelberg

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Xiangwei, K., Feishi, C., Zhiyuan, L., Shaoxiang, Z. (2003). Estimation of Sea Ice Movement Using Locally Parallel Matching Model. In: Palade, V., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2003. Lecture Notes in Computer Science(), vol 2773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45224-9_87

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  • DOI: https://doi.org/10.1007/978-3-540-45224-9_87

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40803-1

  • Online ISBN: 978-3-540-45224-9

  • eBook Packages: Springer Book Archive

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