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Enhanced Landmine Detection from Low Resolution IR Image Sequences

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Computer Analysis of Images and Patterns (CAIP 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5702))

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Abstract

We deal with the problem of landmine field detection using low-resolution infrared (IR) image sequences measured from airborne or vehicle-borne passive IR cameras. The proposed scheme contains two parts: a) employ a multi-scale detector, i.e., a special type of isotropic bandpass filters, to detect landmine candidates in each frame; b) enhance landmine detection through seeking maximum consensus of corresponding landmine candidates over image frames. Experiments were conducted on several IR image sequences measured from airborne and vehicle-borne cameras, where some results are included. As shown in our experiments, the landmine signatures have been significantly enhanced using the proposed scheme, and automatic detection results are reasonably good. These methods can therefore be applied to assisting humanitarian demining work for landmine field detection.

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Author information

Authors and Affiliations

  1. Dept. of Signals and Systems, Chalmers Univ. of Technology, Sweden

    Tiesheng Wang & Irene Yu-Hua Gu

  2. Institute of IPPR, Shanghai Jiao Tong University, Shanghai, China

    Tiesheng Wang

  3. School of Engineering, University of Warwick, United Kingdom

    Tardi Tjahjadi

Authors
  1. Tiesheng Wang
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  2. Irene Yu-Hua Gu
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  3. Tardi Tjahjadi
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Editor information

Editors and Affiliations

  1. Department of Mathematics and Computer Science, University of Münster, Einsteinstrasse 62, 48149, Münster, Germany

    Xiaoyi Jiang

  2. Institute of Mathematics and Computing Science, University of Groningen, Nijenborgh 9, 9747, Groningen, AG, The Netherlands

    Nicolai Petkov

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© 2009 Springer-Verlag Berlin Heidelberg

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Wang, T., Gu, I.YH., Tjahjadi, T. (2009). Enhanced Landmine Detection from Low Resolution IR Image Sequences. In: Jiang, X., Petkov, N. (eds) Computer Analysis of Images and Patterns. CAIP 2009. Lecture Notes in Computer Science, vol 5702. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03767-2_150

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  • DOI: https://doi.org/10.1007/978-3-642-03767-2_150

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03766-5

  • Online ISBN: 978-3-642-03767-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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