• DocumentCode
    3240676
  • Title

    M-SIFT: A new method for Vehicle Logo Recognition

  • Author

    Psyllos, A. ; Anagnostopoulos, Christos-Nikolaos ; Kayafas, Eleftherios

  • Author_Institution
    Sc. of Appl. Math. & Phys. Sci., NTUA, Athens, Greece
  • fYear
    2012
  • fDate
    24-27 July 2012
  • Firstpage
    261
  • Lastpage
    266
  • Abstract
    In this paper, a new algorithm for Vehicle Logo Recognition is proposed, on the basis of an enhanced Scale Invariant Feature Transform (Merge-SIFT or M-SIFT). The algorithm is assessed on a set of 1500 logo images that belong to 10 distinctive vehicle manufacturers. A series of experiments are conducted, splitting the 1500 images to a training set (database) and to a testing set (query). It is shown that the MSIFT approach, which is proposed in this paper, boosts the recognition accuracy compared to the standard SIFT method. The reported results indicate an average of 94.6% true recognition rate in vehicle logos, while the processing time remains low (~0.8sec).
  • Keywords
    image recognition; transforms; vehicles; M-SIFT; merge-scale invariant feature transform; vehicle logo recognition; vehicle manufacturer; Databases; Equations; Feature extraction; Image recognition; Mathematical model; Transforms; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Vehicular Electronics and Safety (ICVES), 2012 IEEE International Conference on
  • Conference_Location
    Istanbul
  • Print_ISBN
    978-1-4673-0992-9
  • Type

    conf

  • DOI
    10.1109/ICVES.2012.6294277
  • Filename
    6294277