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논문 기본 정보

자료유형
학술저널
저자정보
Liu, Yufei (Key Laboratory of Civil Engineering Safety and Durability of Ministry of Education, Department of Civil Engineering, Tsinghua University) Cho, Soojin (School of Urban and Environmental Engineering, U/san National Institute of Science and Technology) Spencer, Billie F. Jr (Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign) Fan, Jiansheng (Key Laboratory of Civil Engineering Safety and Durability of Ministry of Education, Department of Civil Engineering, Tsinghua University)
저널정보
테크노프레스 Smart structures and systems Smart structures and systems 제14권 제4호
발행연도
2014.1
수록면
719 - 741 (23page)

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Monitoring surface cracks is important to ensure the health of concrete structures. However, traditional visual inspection to monitor the concrete cracks has disadvantages such as subjective inspection nature, associated time and cost, and possible danger to inspectors. To alter the visual inspection, a complete procedure for automated crack assessment based on adaptive digital image processing has been proposed in this study. Crack objects are extracted from the images using the subtraction with median filter and the local binarization using the Niblack's method. To adaptively. determine the optimal window sizes for the median filter and the Niblack's method without distortion of crack object an optimal filter size index (OFSI) is proposed. From the extracted crack objects using the optimal size of window, the crack objects are decomposed to the crack skeletons and edges, and the crack width is calculated using 4-connected normal line according to the orientation of the local skeleton line. For an image, a crack width nephogram is obtained to have an intuitive view of the crack distribution. The proposed procedure is verified from a test on a concrete reaction wall with various types of cracks. From the crack images with different crack widths and patterns, the widths of cracks in the order of submillimeters are calculated with high accuracy.

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