Bridge Pillar Defect Detection using Close Range Thermography Imagery

Currently, radiometric thermography image has been explored adequately as alternative advance Non-Destructive Testing (NDT) especially for early detection analysis in various applications. Systematic image calibration, higher spatial resolution and high degree order image processing, thermography im...

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Bibliographic Details
Published in:International Journal of Advanced Computer Science and Applications
Main Author: Rasib A.W.; Yaacob M.L.M.; Idris N.H.; Zainuddin K.; Dollah R.; Yusof N.M.; Rahaman N.A.; Ahmad S.; Hamid N.A.; Mhapo A.M.
Format: Article
Language:English
Published: Science and Information Organization 2022
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129920918&doi=10.14569%2fIJACSA.2022.0130470&partnerID=40&md5=7a782d2de34f85cb9f06d5c3b755fd30
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Summary:Currently, radiometric thermography image has been explored adequately as alternative advance Non-Destructive Testing (NDT) especially for early detection analysis in various applications. Systematic image calibration, higher spatial resolution and high degree order image processing, thermography imagery potential to be used in concrete structure defect detection. Therefore, this study is carried out to examine the defect on bridge pillar surface concrete using drone-based thermography sensor (7-13 pm). Close range remote sensing NDT based on drone platform and imagery segmentation analysis have been applied to interpret the crack line on two pillars at North-South Expressway Central Link (ELITE) Highway. As a result, thermography imagery segmentation and support by multispectral radiometric imagery (RGB) successfully to delineate the micro crack line on the bridge pillar concrete using K-means clustering method. Overall, this study successfully shows the higher order optional platform using drone and thermography sensor that potentially to be applied in forensic concrete structure defect detection for tall structure building. © 2022. All Rights Reserved.
ISSN:2158107X
DOI:10.14569/IJACSA.2022.0130470