Traffic sign recognition and analysis for intelligent vehicles

A. de la Escalera, J.M. Armingol, M. Mata

    Research output: Contribution to journalArticle

    Abstract

    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.
    Original languageEnglish
    Pages (from-to)247-258
    Number of pages12
    JournalImage and Vision Computing
    Volume21
    Issue number3
    DOIs
    Publication statusPublished - 1 Mar 2003

    Fingerprint

    Advanced driver assistance systems
    Traffic signs
    Intelligent vehicle highway systems
    Object recognition
    Invariance
    Lighting
    Genetic algorithms
    Color
    Neural networks

    Keywords

    • object recognition
    • genetic algorithms
    • neural networks
    • traffic sign recognition
    • driver support systems
    • intelligent vehicles
    • intelligent transportation systems

    Cite this

    de la Escalera, A. ; Armingol, J.M. ; Mata, M. / Traffic sign recognition and analysis for intelligent vehicles. In: Image and Vision Computing. 2003 ; Vol. 21, No. 3. pp. 247-258.
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    Traffic sign recognition and analysis for intelligent vehicles. / de la Escalera, A.; Armingol, J.M.; Mata, M.

    In: Image and Vision Computing, Vol. 21, No. 3, 01.03.2003, p. 247-258.

    Research output: Contribution to journalArticle

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