This paper deals with the fast and robust detection of the traffic sign images. A new technique called geometric fragmentation is proposed to detect the red circular traffic signs. It detects the outer ellipses of the signs by combining the left and right fragments of the ellipse objects. A search based on the geometric fragmentation is used to find the ellipse fragments. This search is somewhat similar to genetic algorithm (GA) in the sense that it employs the terms of individual, population, crossover, and objective function usually used in GA. To increase the accuracy and reduce the computational time, a new objective function is introduced for evaluating the individuals. The algorithm was tested for detecting the red circular traffic signs from the real scene image. The experimental results show that the proposed algorithm has a higher detection rate with a lower computational cost compared with the referential genetic algorithm-based ellipse detection.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Fast and robust traffic sign detection


    Contributors:
    Soetedjo, A. (author) / Yamada, K. (author)


    Publication date :

    2005


    Size :

    6 Seiten, 10 Quellen




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




    Robust traffic sign detection in complex road environments

    Tian, Bin / Chen, Ran / Yao, Yanjie et al. | IEEE | 2016


    Local Contour Patterns for fast traffic sign detection

    Parada-Loira, Francisco / Alba-Castro, José L | IEEE | 2010


    Traffic Sign Detection

    Escalera, Sergio / Baró, Xavier / Pujol, Oriol et al. | Springer Verlag | 2011


    Occlusion-robust traffic sign detection via cascaded colour cubic feature

    Liu, Chunsheng / Chang, Faliang / Liu, Chenyun | IET | 2016

    Free access

    Occlusion‐robust traffic sign detection via cascaded colour cubic feature

    Liu, Chunsheng / Chang, Faliang / Liu, Chenyun | Wiley | 2016

    Free access