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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    Title :

    Traffic signs recognition based on PCA-SIFT


    Contributors:
    Gao, Hongwei (author) / Liu, Chuanyin (author) / Yu, Yang (author) / Li, Bin (author)


    Publication date :

    2014-06-01


    Size :

    1064103 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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