Improved percolation-based method for crack detection in concrete surface images

Yamaguchi Tomoyuki, Hashimoto Shuji

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

    11 Citations (Scopus)

    Abstract

    This paper presents a highly accurate and efficient method for crack detection using percolation-based image processing. The detection of cracks in concrete surfaces during the maintenance and diagnosis of concrete structures is important to ensure the safety of these structures. Recently, the image-based crack detection method has attracted considerable attention due to its low cost and objectivity. However, there are several problems in the practical application of image processing for crack detection since real concrete surface images have noises such as concrete blebs, stains, and shadings of several sizes. In order to resolve these problems, our proposed method focuses on the number of pixels in a crack and the connectivity of the pixels. Our method employs a percolation model for crack detection in order to consider the features of the cracks. Through experiments using real concrete surface images, we demonstrate the accuracy and efficiency of our method.

    Original languageEnglish
    Title of host publicationProceedings - International Conference on Pattern Recognition
    Publication statusPublished - 2008
    Event2008 19th International Conference on Pattern Recognition, ICPR 2008 - Tampa, FL
    Duration: 2008 Dec 82008 Dec 11

    Other

    Other2008 19th International Conference on Pattern Recognition, ICPR 2008
    CityTampa, FL
    Period08/12/808/12/11

    ASJC Scopus subject areas

    • Computer Vision and Pattern Recognition

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  • Cite this

    Tomoyuki, Y., & Shuji, H. (2008). Improved percolation-based method for crack detection in concrete surface images. In Proceedings - International Conference on Pattern Recognition [4761627]