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

Tomoyuki Yamaguchi*, Shuji Hashimoto

*この研究の対応する著者

    研究成果: Conference contribution

    42 被引用数 (Scopus)

    抄録

    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.

    本文言語English
    ホスト出版物のタイトルIECON Proceedings (Industrial Electronics Conference)
    ページ3355-3360
    ページ数6
    DOI
    出版ステータスPublished - 2006
    イベントIECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics - Paris
    継続期間: 2006 11 62006 11 10

    Other

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

    ASJC Scopus subject areas

    • 電子工学および電気工学

    フィンガープリント

    「Automated crack detection for concrete surface image using percolation model and edge information」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

    引用スタイル