This paper deals with object recognition in outdoor environments. In this type of environments, lighting conditions cannot be controlled and predicted, objects can be partially occluded, and their position and orientation is not known a priori. The chosen type of objects is traffic or road signs, due to their usefulness for sign maintenance, inventory in highways and cities, driver support systems and intelligent autonomous vehicles. A genetic algorithm is used for the detection step, allowing an invariance localisation to changes in position, scale, rotation, weather conditions, partial occlusion, and the presence of other objects of the same colour. A neural network achieves the classification. The global system not only recognises the traffic sign but also provides information about its condition or state.


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    Titel :

    Traffic sign recognition and analysis for intelligent vehicles


    Beteiligte:
    Escalera, A. de la (Autor:in) / Armingol, J.M. (Autor:in) / Mata, M. (Autor:in)

    Erschienen in:

    Image and Vision Computing ; 21 , 3 ; 247-258


    Erscheinungsdatum :

    2003


    Format / Umfang :

    12 Seiten, 40 Quellen




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch




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