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Target Depth and Metal Type Discrimination with Cost Based Probability Updating

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Agent and Multi-Agent Systems. Technologies and Applications (KES-AMSTA 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7327))

Abstract

This paper presents a cost based probability updating technique based on Bayesian decision theory for modifying decision confidences. The technique allows for the incorporation of prior knowledge via the use of cost matrices supplied by another source of intelligence. Data signals acquired by a metal detector array corresponding to UXO based targets were used to evaluate the technique with the assistance of a previously developed automated decision system. The classification classes utilised were based on target depth level and metal type. The results showed that the probability updating technique was able to produce an increase in the classification performance and also reduce the classification errors below approximately 5 to 10%.

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Author information

Authors and Affiliations

  1. Knowledge-Based Intelligent Engineering Systems (KES) Centre, School of Electrical and Information Engineering, University of South Australia, Australia

    Minh Dao-Johnson Tran & Lakhmi C. Jain

  2. Threat Mitigation Group, Weapon Systems Division, Defence Science and Technology Organisation (DSTO), Australia

    Canicious Abeynayake

Authors
  1. Minh Dao-Johnson Tran
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  2. Canicious Abeynayake
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  3. Lakhmi C. Jain
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Editor information

Editors and Affiliations

  1. Faculty of Electrical Engineering and Computing, University of Zagreb, Unska 3, 10000, Zagreb, Croatia

    Gordan Jezic  & Mario Kusek  & 

  2. Institute of Informatics (I-32), Division of Knowledge Management Systems, Wroclaw University of Technology, Str. Wyb. Wyspianskiego 27, 50-370, Wroclaw, Poland

    Ngoc-Thanh Nguyen

  3. KES International, Shoreham-by-sea, P.O. Box 2115, BN43 9AF, UK

    Robert J. Howlett

  4. School of Electrical and Information Engineering, University of South Australia, Mawson Lakes Campus, 5095, Adelaide, SA, Australia

    Lakhmi C. Jain

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© 2012 Springer-Verlag Berlin Heidelberg

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Tran, M.DJ., Abeynayake, C., Jain, L.C. (2012). Target Depth and Metal Type Discrimination with Cost Based Probability Updating. In: Jezic, G., Kusek, M., Nguyen, NT., Howlett, R.J., Jain, L.C. (eds) Agent and Multi-Agent Systems. Technologies and Applications. KES-AMSTA 2012. Lecture Notes in Computer Science(), vol 7327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30947-2_44

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  • DOI: https://doi.org/10.1007/978-3-642-30947-2_44

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-30946-5

  • Online ISBN: 978-3-642-30947-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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