Automated crack detection for concrete surface image using percolation model and edge information

Tomoyuki Yamaguchi, Shuji Hashimoto

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    31 Citations (Scopus)

    Abstract

    A crack Is an important indicator in concrete structure diagnosis. Although cracks tend to display linear characteristics, it is not easy to detect them by conventional methods. There are a variety of difficult sources of noise: concrete bleb, stain noise, insufficient contrast, and shadings. In this paper, we introduce a novel crack detection method for a concrete surface image based on a percolation model. Our method evaluates the central pixel in a local window according to a cluster formed using percolation processing. In addition, we describe reducing the computational burden while still preserving the precision of the crack detection. To achieve this, our method utilizes edge information to reduce the number of starting points for percolation processing. The validity of the proposed technique is investigated through experiments with images of real concrete surfaces and it is shown that robust and reliable crack detection without oversight is achieved.

    Original languageEnglish
    Title of host publicationIECON Proceedings (Industrial Electronics Conference)
    Pages3355-3360
    Number of pages6
    DOIs
    Publication statusPublished - 2006
    EventIECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics - Paris
    Duration: 2006 Nov 62006 Nov 10

    Other

    OtherIECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics
    CityParis
    Period06/11/606/11/10

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    ASJC Scopus subject areas

    • Electrical and Electronic Engineering

    Cite this

    Yamaguchi, T., & Hashimoto, S. (2006). Automated crack detection for concrete surface image using percolation model and edge information. In IECON Proceedings (Industrial Electronics Conference) (pp. 3355-3360). [4153629] https://doi.org/10.1109/IECON.2006.348070