Options
Regionally enhanced multiphase segmentation technique for damaged surfaces
Date Issued
2014-09-15
Date Available
2019-05-13T11:21:54Z
Abstract
Imaging‐based damage detection techniques are increasingly being utilized alongside traditional visual inspection methods to provide owners/operators of infrastructure with an efficient source of quantitative information for ensuring their continued safe and economic operation. However, there exists scope for significant development of improved damage detection algorithms that can characterize features of interest in challenging scenes with credibility. This article presents a new regionally enhanced multiphase segmentation (REMPS) technique that is designed to detect a broad range of damage forms on the surface of civil infrastructure. The technique is successfully applied to a corroding infrastructure component in a harbour facility. REMPS integrates spatial and pixel relationships to identify, classify, and quantify the area of damaged regions to a high degree of accuracy. The image of interest is preprocessed through a contrast enhancement and color reduction scheme. Features in the image are then identified using a Sobel edge detector, followed by subsequent classification using a clustering‐based filtering technique. Finally, support vector machines are used to classify pixels which are locally supplemented onto damaged regions to improve their size and shape characteristics. The performance of REMPS in different color spaces is investigated for best detection on the basis of receiver operating characteristics curves. The superiority of REMPS over existing segmentation approaches is demonstrated, in particular when considering high dynamic range imagery. It is shown that REMPS easily extends beyond the application presented and may be considered an effective and versatile standalone segmentation technique.
Sponsorship
Irish Research Council for Science, Engineering and Technology
Type of Material
Journal Article
Publisher
Wiley Online Library
Journal
Computer-Aided Civil and Infrastructure Engineering
Volume
29
Issue
9
Start Page
644
End Page
658
Copyright (Published Version)
2014 Computer-Aided Civil and Infrastructure Engineering
Language
English
Status of Item
Peer reviewed
ISSN
1093-9687
This item is made available under a Creative Commons License
File(s)
Owning collection
Scopus© citations
52
Acquisition Date
Mar 28, 2024
Mar 28, 2024
Views
699
Last Week
2
2
Last Month
2
2
Acquisition Date
Mar 28, 2024
Mar 28, 2024
Downloads
584
Last Week
2
2
Last Month
13
13
Acquisition Date
Mar 28, 2024
Mar 28, 2024