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Automatic classification of GPR signals

Conference Paper


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Abstract


  • Ground penetrating radar has been widely used in many areas. However, the processing and interpretation of acquired signals remains a challenging task since it requires experienced users to manage the whole operations. In this paper, we propose an automatic classification system to categorise GPR signals based on magnitude spectrum amplitudes and support vector machines. The system is tested on a real-world GPR

    data set. The experimental results show that our system can correctly distinguish ground penetrating radar signals reflected by different materials.

Publication Date


  • 2010

Citation


  • Shao, W., Bouzerdoum, A., Phung, S. Lam., Su, L., Indraratna, B. & Rujikiatkamjorn, C. (2010). Automatic classification of GPR signals. International Conference on Ground Penetrating Radar (pp. 1-6). USA: IEEE.

Scopus Eid


  • 2-s2.0-77956550871

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=1844&context=infopapers

Ro Metadata Url


  • http://ro.uow.edu.au/infopapers/831

Has Global Citation Frequency


Start Page


  • 1

End Page


  • 6

Place Of Publication


  • USA

Abstract


  • Ground penetrating radar has been widely used in many areas. However, the processing and interpretation of acquired signals remains a challenging task since it requires experienced users to manage the whole operations. In this paper, we propose an automatic classification system to categorise GPR signals based on magnitude spectrum amplitudes and support vector machines. The system is tested on a real-world GPR

    data set. The experimental results show that our system can correctly distinguish ground penetrating radar signals reflected by different materials.

Publication Date


  • 2010

Citation


  • Shao, W., Bouzerdoum, A., Phung, S. Lam., Su, L., Indraratna, B. & Rujikiatkamjorn, C. (2010). Automatic classification of GPR signals. International Conference on Ground Penetrating Radar (pp. 1-6). USA: IEEE.

Scopus Eid


  • 2-s2.0-77956550871

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=1844&context=infopapers

Ro Metadata Url


  • http://ro.uow.edu.au/infopapers/831

Has Global Citation Frequency


Start Page


  • 1

End Page


  • 6

Place Of Publication


  • USA