Multi-class Vehicle Type Recognition System

  • Xavier Clady
  • Pablo Negri
  • Maurice Milgram
  • Raphael Poulenard
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5064)


This paper presents a framework for multiclass vehicle type (Make and Model) identification based on oriented contour points. A method to construct a model from several frontal vehicle images is presented. Employing this model, three voting algorithms and a distance error allows to measure the similarity between an input instance and the data bases classes. These scores could be combined to design a discriminant function. We present too a second classification stage that employ scores like vectors. A nearest-neighbor algorithm is used to determine the vehicle type. This method have been tested on a realistic data set (830 images containing 50 different vehicle classes) obtaining similar results for equivalent recognition frameworks with different features selections [12]. The system also shows to be robust to partial occlusions.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Xavier Clady
    • 1
  • Pablo Negri
    • 1
  • Maurice Milgram
    • 1
  • Raphael Poulenard
    • 2
  1. 1.Institut des Systèmes Intelligents et RobotiqueUniversité Pierre et Marie Curie-Paris 6, CNRS FRE 2907 
  2. 2.LPR Editor - Montpellier 

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