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Title: Comparative analysis of image binarization methods for crack identification in concrete structures

Abstract

Surface cracks in concrete structures are critical indicators of structural damage and durability. Manual visual inspection, the most commonly used method in practice, is inefficient from cost, time, accuracy, and safety perspectives. A promising alternative is computer vision-based methods that can automatically extract crack information from images. Image binarization, developed for text detection, is appropriate for crack identification, as texts and cracks are similar, consisting of distinguishable lines and curves. However, standardizing crack identification using image binarization is challenging, because binarization depends on the method and associated parameters. We investigate image binarization for crack identification, focusing on optimal parameter determination and comparative performance evaluation for five common binarization methods. Crack images are prepared to obtain optimal parameters by minimizing errors in estimated crack widths. Subsequently, comparative analysis is conducted using crack images with different conditions based on three performance evaluation criteria: crack width and length measurement accuracy and computation time.

Authors:
 [1];  [1];  [2];  [1];  [1]
  1. School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan (Korea, Republic of)
  2. Department of Civil Engineering, University of Seoul, Seoul (Korea, Republic of)
Publication Date:
OSTI Identifier:
22701566
Resource Type:
Journal Article
Journal Name:
Cement and Concrete Research
Additional Journal Information:
Journal Volume: 99; Other Information: Copyright (c) 2017 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0008-8846
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE; CALCULATION METHODS; COMPARATIVE EVALUATIONS; CONCRETES; CRACKS; IMAGE PROCESSING

Citation Formats

Kim, Hyunjun, Ahn, Eunjong, Cho, Soojin, Shin, Myoungsu, and Sim, Sung-Han. Comparative analysis of image binarization methods for crack identification in concrete structures. United States: N. p., 2017. Web. doi:10.1016/J.CEMCONRES.2017.04.018.
Kim, Hyunjun, Ahn, Eunjong, Cho, Soojin, Shin, Myoungsu, & Sim, Sung-Han. Comparative analysis of image binarization methods for crack identification in concrete structures. United States. doi:10.1016/J.CEMCONRES.2017.04.018.
Kim, Hyunjun, Ahn, Eunjong, Cho, Soojin, Shin, Myoungsu, and Sim, Sung-Han. Fri . "Comparative analysis of image binarization methods for crack identification in concrete structures". United States. doi:10.1016/J.CEMCONRES.2017.04.018.
@article{osti_22701566,
title = {Comparative analysis of image binarization methods for crack identification in concrete structures},
author = {Kim, Hyunjun and Ahn, Eunjong and Cho, Soojin and Shin, Myoungsu and Sim, Sung-Han},
abstractNote = {Surface cracks in concrete structures are critical indicators of structural damage and durability. Manual visual inspection, the most commonly used method in practice, is inefficient from cost, time, accuracy, and safety perspectives. A promising alternative is computer vision-based methods that can automatically extract crack information from images. Image binarization, developed for text detection, is appropriate for crack identification, as texts and cracks are similar, consisting of distinguishable lines and curves. However, standardizing crack identification using image binarization is challenging, because binarization depends on the method and associated parameters. We investigate image binarization for crack identification, focusing on optimal parameter determination and comparative performance evaluation for five common binarization methods. Crack images are prepared to obtain optimal parameters by minimizing errors in estimated crack widths. Subsequently, comparative analysis is conducted using crack images with different conditions based on three performance evaluation criteria: crack width and length measurement accuracy and computation time.},
doi = {10.1016/J.CEMCONRES.2017.04.018},
journal = {Cement and Concrete Research},
issn = {0008-8846},
number = ,
volume = 99,
place = {United States},
year = {2017},
month = {9}
}