• DocumentCode
    1598754
  • Title

    Classification of moving vehicle using multi-frame time domain features

  • Author

    Paulraj, M.P. ; Adom, Abdul Hamid ; Sundararaj, Sathishkumar

  • Author_Institution
    School of Mechatronic Engineering, Universiti Malaysia Perlis, Ulu Pauh Campus, 02600, Malaysia
  • fYear
    2013
  • Firstpage
    529
  • Lastpage
    533
  • Abstract
    This research work is mainly focused on recognition of different vehicles and its position using acoustic sound source to assist the Differentially Hearing Ability Abled (DHAA). In this paper, a simple protocol has been designed to record the noise emanated by the moving vehicles under different weather conditions and also at different vehicle speed. Two feature extraction methods namely Auto regressive and statistical feature methods are used to extract the features from the recorded acoustic signature. The Radial Basis Function Network (RBFN) model was used for classification. The networks effectiveness has been validated through stimulation.
  • Keywords
    Accuracy; Biology; Auto Regressive Model; Differentially Hearing Ability Abled (DHAA); Radial Basis Function Network (RBFN); Statistical Features;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems and Control (ISCO), 2013 7th International Conference on
  • Conference_Location
    Coimbatore, Tamil Nadu, India
  • Print_ISBN
    978-1-4673-4359-6
  • Type

    conf

  • DOI
    10.1109/ISCO.2013.6481211
  • Filename
    6481211