Performance analysis of various types of surface crack detection based on image processing

SINERGI

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Field Value
 
Title Performance analysis of various types of surface crack detection based on image processing
 
Creator Lionnie, Regina
Ramadhan, Rizky Citra
Rosyadi, Ahmad Syadidu
Jusoh, Muzammil
Alaydrus, Mudrik
 
Subject
Corrosion Crack Image; Early Thermal Crack Image; Mathematical Morphology; Otsu Thresholding; Plastic Shrinkage Crack Image;
 
Description Major cracks on a highway or bridge's concrete surface have a massive risk of damages, accompanied by less maintenance, slow detection, and handling; the worst case of the damage is the structure's total collapse, which can produce fatalities. Moreover, Indonesia's climate and geographical location contribute to a higher level of potential damage to the structure. In order to reduce the potential damage, the need for a surface crack detection system arises. This research analysed three different databases (Database A, B, and C) with different surface concrete crack types, such as early thermal contraction, plastic shrinkage, corrosion reinforcement, and non-crack images. The total images from each Database vary from 14 images for Database A, 80 images for Database B, and 4000 images for Database C. The Otsu thresholding and mathematical morphology operations such as opening, closing, dilation, and erosion with pre-processing methods were combined and produced results for each Database with classification using Euclidean distance calculation. The best results for Database A and B were 100% using combination Otsu thresholding with Laplacian operator and Laplacian of Gaussian filter and the same result for a combination of mathematical morphological operations. The best result using Database C, which had more images than Database A and B, was 80,2% using a combination of mathematical morphological operations. 
 
Publisher Universitas Mercu Buana
 
Contributor
 
Date 2021-11-18
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Identifier https://publikasi.mercubuana.ac.id/index.php/sinergi/article/view/11195
10.22441/sinergi.2022.1.001
 
Source SINERGI; Vol 26, No 1 (2022); 1-6
24601217
14102331
 
Language en
 
Rights Copyright (c) 2022 SINERGI
 

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