• DocumentCode
    2301171
  • Title

    Vehicle-logo Recognition Method Based on Tchebichef Moment Invariants and SVM

  • Author

    Dai, Shijie ; Huang, He ; Gao, Zhangying ; Li, Kai ; Xiao, Shumei

  • Author_Institution
    Res. Inst. of Robot. & Autom., Hebei Univ. of Technol., Tianjin, China
  • Volume
    3
  • fYear
    2009
  • fDate
    19-21 May 2009
  • Firstpage
    18
  • Lastpage
    21
  • Abstract
    In order to solve the problem about the recognition accuracy, Tchebichef moment invariants and support vector machine (SVM) are adopted to recognize the vehicle-logo. It extracts six invariant moments of the object as feature vectors, and then uses the support vector machines (SVM) to recognize vehicle-logo. Tchebichef moment invariants perform significantly better than Hu moment invariants and Zernike moment invariants. The result of these experiments suggests that this system has a high recognition rate in both noise-free and noisy environment which has high practical value.
  • Keywords
    automated highways; feature extraction; image recognition; method of moments; road vehicles; support vector machines; Hu moment invariant; SVM; Tchebichef moment invariant; Zernike moment invariant; feature vector extraction; object extraction; support vector machine; vehicle-logo recognition method; Licenses; Noise shaping; Polynomials; Redundancy; Robotics and automation; Shape; Software engineering; Support vector machines; Vehicles; Working environment noise; Support vector machines; Tchebichef moment invariants; vehicle-logo recognition (VLR);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering, 2009. WCSE '09. WRI World Congress on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-0-7695-3570-8
  • Type

    conf

  • DOI
    10.1109/WCSE.2009.263
  • Filename
    5319356