System principle and composition including image acquisition, image processing and image interpretation for pavement crack automatic recognition based on digital image processing are presented. In order to improve crack identification rate, pavement image retrogression reasons are introduced and stochastic and complex characteristics for pavement images are analyzed. Wiener filtering theory is investigated to overcome the problem that some classical methods will weaken useful image details when restrain noise. Results show that Wiener filtering can preserve image edge information and remove some noise from non-uniform illumination, imaging systems, pavement material and grain's texture through the analysis for representative examples.


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    Title :

    Pavement Crack Automatic Recognition Based on Wiener Filtering


    Contributors:
    Zhang, J. (author) / Sha, A. (author) / Sun, Z. Y. (author) / Gao, H. G. (author)

    Conference:

    Ninth International Conference of Chinese Transportation Professionals (ICCTP) ; 2009 ; Harbin, China


    Published in:

    Publication date :

    2009-07-23




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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