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Concrete Crack Detection by Multiple Sequential Image Filtering

delete2011-03-29
delete317
PRE
AI
J
Junji Yoshida
Y
Yozo Fujino
DOI:10.1111/j.1467-8667.2011.00716.xdelete
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Abstract

Abstract

En 中文
This article presents a new robust automated image processing method for detecting cracks in surface images of concrete structures. This method involves two steps: (1) development of an image filter for detecting major cracks using genetic programming (GP), and (2) elimination of residual noise after filtering and detection of indistinct cracks by iterative applications of the image filter to the local regions surrounding the cracks. The proposed method can be used for the accurate detection of cracks in surface images recorded under various conditions. Moreover, the widths of the detected cracks can be quantified on the basis of the spatial derivatives of the brightness patterns. The estimated crack widths are in good agreement with those measured manually.
Keywords:
GENETIC ALGORITHM
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

C
Computer-Aided Civil and Infrastructure Engineering
IF:
9.1
Papers:
2.0K
Citations:
10.0K

Organization

U
University of Tokyo
Scholars:
7.1W
Papers: 6.5W
Citations: 2.2K
U
University of Yamanashi
Scholars:
4.2K
Papers: 3.4K
Citations: 2.7K
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