Traffic signs automatic recognition was researched in this paper. Traffic signs image preprocessing methods was introduced firstly. Secondly, feature extraction algorithm of traffic signs based on SIFT was elaborated, then a fast SIFT algorithm based on PCA dimensionality reduction was presented to extract the characteristics of traffic signs. Finally, the SVM classifier was studied. A large number of experimental results were completed to demonstrate the effectiveness and practicality of related algorithms.


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    Titel :

    Traffic signs recognition based on PCA-SIFT


    Beteiligte:
    Gao, Hongwei (Autor:in) / Liu, Chuanyin (Autor:in) / Yu, Yang (Autor:in) / Li, Bin (Autor:in)


    Erscheinungsdatum :

    01.06.2014


    Format / Umfang :

    1064103 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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