In modern traffic surveillance, computer vision methods are often employed to detect vehicles of interest because of the rich information content contained in an image. In this paper, we propose an efficient method for extracting the boundary of vehicles free from their moving cast shadows and reflective regions. The extraction method is based on the hypothesis that regions of similar texture are less discriminative, disregarding intensity differences between the vehicle body and the cast shadow or reflection on the vehicle. In this novel algorithm, a united likelihood map that based on the relationship of texture, luminance and chrominance of each pixel is initially constructed. Subsequently, a foreground mask is constructed by applying morphological operations. Vehicles can be successfully extracted and different vehicle components can be efficiently distinguished by the related autocorrelation index within the vehicle mask. ; published_or_final_version


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Vehicle feature extraction by patch-based sampling


    Beteiligte:
    Lam, WWL (Autor:in) / Pang, CCC (Autor:in) / Yung, NHC (Autor:in)

    Erscheinungsdatum :

    2003-01-01



    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629



    Vehicle feature extraction by patch-based sampling

    Lam, William W. L. / Pang, Clement C. C. / Yung, Nelson H. C. | SPIE | 2003


    Stereo vision-based feature extraction for vehicle detection

    Bensrhair, A. / Bertozzi, A. / Broggi, A. et al. | IEEE | 2002


    Stereo Vision-based Feature Extraction for Vehicle Detection

    Bensrhair, A. / Bertozzi, M. / Broggi, A. et al. | British Library Conference Proceedings | 2003


    Vehicle track prediction method based on drivable area feature extraction

    ZHANG ZHEN / XIAO ZHONGWEN | Europäisches Patentamt | 2023

    Freier Zugriff