• DocumentCode
    1606115
  • Title

    Automatic classification of GPR signals

  • Author

    Shao, W. ; Bouzerdoum, A. ; Phung, S.L. ; Su, L. ; Indraratna, B. ; Rujikiatkamjorn, C.

  • Author_Institution
    Sch. of Electr., Comput. & Telecommun. Eng., Univ. of Wollongong, Wollongong, NSW, Australia
  • fYear
    2010
  • Firstpage
    1
  • Lastpage
    6
  • 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.
  • Keywords
    ground penetrating radar; radar signal processing; signal classification; support vector machines; GPR signal classification; ground penetrating radar; magnitude spectrum amplitudes; support vector machines; Electromagnetic scattering; Face detection; Filtering; Fourier transforms; Frequency; Ground penetrating radar; Humans; Low pass filters; Support vector machine classification; Support vector machines; GPR; SVM; classification; magnitude spectrum;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Ground Penetrating Radar (GPR), 2010 13th International Conference on
  • Conference_Location
    Lecce
  • Print_ISBN
    978-1-4244-4604-9
  • Electronic_ISBN
    978-1-4244-4605-6
  • Type

    conf

  • DOI
    10.1109/ICGPR.2010.5550187
  • Filename
    5550187