• DocumentCode
    1711971
  • Title

    Improving similarity measures for re-identification of vehicles using AMR sensors

  • Author

    Cirilo Gimeno, Ramon V. ; Garcia Celda, Antonio ; Pla-Castells, Marta ; Martinez Plume, Javier

  • Author_Institution
    Robot. & Inf. & Commun. Technol. Inst., Univ. of Valencia, Paterna, Spain
  • fYear
    2013
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    The use of Anisotropic Magneto-Resistive (AMR) sensors for road traffic monitoring has gained popularity in recent years. The Earth magnetic field variations caused by vehicles passing over this kind of sensors can be measured and used for various purposes, including vehicle re-identification at different sensing zones. AMR sensors provide data that allow the calculation of traffic parameters by using simple signal processing techniques. But when vehicle re-identification is the objective, it is not clear which is the best method to compare the signals from different sensors in order to know whether or not they belong to the same vehicle. This paper presents an experimental study with the objective of determining the optimal similarity measure function for AMR sensors signals when used for vehicle re-identification.
  • Keywords
    enhanced magnetoresistance; geomagnetism; magnetic sensors; magnetoresistive devices; road traffic; signal processing; traffic engineering computing; AMR sensor signals; AMR sensors; Earth magnetic field variations; anisotropic magneto-resistive sensors; optimal similarity measure function; road traffic monitoring; signal processing techniques; traffic parameter calculation; vehicle re-identification; Magnetic field measurement; Magnetic sensors; Monitoring; Roads; Vehicles; AMR; similarity measures; vehicle re-identification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information, Communications and Signal Processing (ICICS) 2013 9th International Conference on
  • Conference_Location
    Tainan
  • Print_ISBN
    978-1-4799-0433-4
  • Type

    conf

  • DOI
    10.1109/ICICS.2013.6782837
  • Filename
    6782837