In autonomous driving, road markings are an essential element for high-precision mapping, trajectory planning and can provide important information for localization. This paper presents an approach to detect, classify and approximate a great variety of road markings using a stereoscopic camera system. We present an algorithm that is able to classify characters and arrows as well as stop-lines, pedestrian crossings, dashed and straight lines, etc. The classification is independent of orientation, position or the exact shape. This is achieved using a histogram of the marking width as main part of the feature vector for line-shaped markings and Optical Character Recognition (OCR) for characters. Classification is done by an Artificial Neural Network (ANN). We have evaluated our approach over a 10.5 km drive through an urban area.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    A Universal Approach to Detect and Classify Road Surface Markings


    Beteiligte:


    Erscheinungsdatum :

    01.09.2015


    Format / Umfang :

    1996512 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Self-driving system for smart road markings and smart road markings

    LEE SUK KI / KIM YONG SEOK / PARK WON IL et al. | Europäisches Patentamt | 2022

    Freier Zugriff

    High performance road markings

    Phillips, K. | British Library Online Contents | 1994



    ROAD MARKINGS COMPRISING FUNCTIONAL COMPONENTS

    TAMINIAU CYRIL JAN RAFAEL MARIE | Europäisches Patentamt | 2020

    Freier Zugriff

    Vehicle localization using road markings

    Wu, Tao / Ranganathan, Ananth | IEEE | 2013