• DocumentCode
    2966276
  • Title

    Vehicle detection with projection histogram and type recognition using hybrid neural networks

  • Author

    Liu, Yiguang ; You, Zbisheng ; Cao, Liping ; Jiang, Xinrong

  • Author_Institution
    Inst. of Image & Graphics, Sichuan Univ., Chengdu, China
  • Volume
    1
  • fYear
    2004
  • fDate
    21-23 March 2004
  • Firstpage
    393
  • Abstract
    Most vehicle head faces have one window, two illuminative lamps and a license plate, a method is proposed using features about them to detect vehicle head face. Edges of window are straight lines commonly, in the projection histogram whose direction is not parallel to window edge, there is an abrupt change at the edge location. This property can be used to locate window candidate position. If lamps and license plate have all been located, the candidate is verified surely and truly. In order to recognize vehicle type, a hybrid neural network is designed to analyze the extracted features. The network contains two parts, the 1st part uses support vector machines, the 2nd part contains four perceptrons which verifies the output of 1st and produces recognized result. Synthetic experiment of this method is given and some discussions have also been made.
  • Keywords
    feature extraction; multilayer perceptrons; object recognition; road vehicles; support vector machines; feature extraction; hybrid neural network; hybrid neural networks; illuminative lamps; license plate; perceptrons; projection histogram; support vector machines; vehicle detection; vehicle head faces; vehicle type recognition; window candidate position; Face detection; Feature extraction; Histograms; Lamps; Licenses; Magnetic heads; Neural networks; Support vector machines; Vehicle detection; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Networking, Sensing and Control, 2004 IEEE International Conference on
  • ISSN
    1810-7869
  • Print_ISBN
    0-7803-8193-9
  • Type

    conf

  • DOI
    10.1109/ICNSC.2004.1297469
  • Filename
    1297469