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The Era of Interactive Media

pp 325-335

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Vehicle Type Classification Using Data Mining Techniques

  • Yu PengAffiliated withThe School of DCIT, University of Newcastle Email author 
  • , Jesse S. JinAffiliated withThe School of DCIT, University of Newcastle
  • , Suhuai LuoAffiliated withThe School of DCIT, University of Newcastle
  • , Min XuAffiliated withFaculty of Eng. & IT, University of Technology
  • , Sherlock AuAffiliated withGlobal Advanced Vison Ltd
  • , Zhigang ZhangAffiliated withSchool of Info., Xi’an University of Finance and Economics
  • , Yue CuiAffiliated withThe School of DCIT, University of Newcastle

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Abstract

In this paper, we proposed a novel and accurate visual-based vehicle type classification system. The system builts up a classifier through applying Support Vector Machine with various features of vehicle image. We made three contributions here: first, we originally incorporated color of license plate in the classification system. Moreover, the vehicle front was measured accurately based on license plate localization and background-subtraction technique. Finally, type probabilities for every vehicle image were derived from eigenvectors rather than deciding vehicle type directly. Instead of calculating eigenvectors from the whole body images of vehicle in existing methods, our eigenvectors are calculated from vehicle front images. These improvements make our system more applicable and accurate. The experiments demonstrated our system performed well with very promising classification rate under different weather or lighting conditions.

Keywords

Vehicle type classification License plate color recognition Vehicle front extraction Eigenvector Type possibility SVM