We propose a novel, real-time framework for traffic sign detection and recognition using a camera mounted on the dashboard of a moving vehicle. Traffic sign detection and recognition plays an important role in Advanced Driver Assistance Systems (ADAS) as it helps increase driving safety. However, it is very challenging to detect and recognize traffic signs because of challenges such as perspective distortion, illumination variation, occlusion and motion blur from moving vehicle. In our framework, we use Hue Saturation Value (HSV) color filtering for traffic sign detection. In our Grassmann manifold based traffic sign recognition framework, we create subspaces of each unique traffic sign. These subspaces accommodate the uncertainties that occur during detection and variations in different instances of the same traffic sign. These subspaces lie on a Grassmann manifold and we use discriminant analysis on Grassmann manifolds for recognising them. We have carried out extensive experiments on multiple publicly available traffic sign datasets and compared our proposed framework with multiple state-of-the-art methods. Experimental results show that our system is robust and has a high degree of accuracy.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A Framework for Real-time Traffic Sign Detection and Recognition using Grassmann Manifolds


    Contributors:


    Publication date :

    2018-11-01


    Size :

    1022501 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English





    Autonomous Traffic Sign Detection and Recognition in Real Time

    Malarvizhi, N. / Jupudi, Athreayasa Kalyan / Velpuri, Manikanta et al. | Springer Verlag | 2023


    Real-Time Traffic-Sign Recognition Using Tree Classifiers

    Zaklouta, Fatin / Stanciulescu, Bogdan | IEEE | 2012


    A Real-Time Traffic Sign Recognition System

    Estable, S. / Schick, J. / Stein, F. et al. | British Library Conference Proceedings | 1994