The detection of road lane markings has many practical applications, such as advanced driver assistance systems, as well as road maintenance. In this paper we propose an algorithm to detect and recognize lane markings from panoramic images. Our system consists of three steps. First after inverse perspective mapping, the potential lane markings are segmented by finding the high-intensity pixels of the image. Second, we extract the inner distance as a feature of each region of interest from the segmented image. Third, we classify features through a Support Vector Machine (SVM). The experiments show that the system is capable of recognizing 97% of the parts of long solid lines and 94% of the dashed lines and can be extended to recognize other road markings such as arrows.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Recognition of Lane Markings in Panoramic Images


    Contributors:
    Li, C. (author) / Creusen, I. (author) / Hazelhoff, L. (author) / With, P.H.N. de (author)


    Publication date :

    2014


    Size :

    6 Seiten, Bilder, 4 Quellen



    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




    Detection and Recognition of Road Markings in Panoramic Images

    Li, Cheng / Creusen, Ivo / Hazelhoff, Lykele et al. | British Library Conference Proceedings | 2015




    Ridgeness for detecting lane markings

    Lopez, A. / Serrat, J. / Saludes, J. et al. | Tema Archive | 2005


    Evaluation of Shared Lane Markings

    W. W. Hunter / L. Thomas / R. Srinivasan et al. | NTIS | 2010