Gabor Filter-Based Segmentation of Railroad Radargrams for Improved Rail Track Condition Assessment: Preliminary Studies and Future Perspectives

Ground penetrating radar (GPR) has been used for several years as a non-contact and non-destructive measurement method for rail track analysis with the aim of recording the condition of ballast and substructures. As the recorded data sets typically cover a distance of many kilometers, the evaluation...

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Autores principales:	Gerald Zauner, David Groessbacher, Martin Buerger, Florian Auer, Giuseppe Staccone
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	ground penetrating radar (GPR) railway track condition assessment image processing 2D Gabor filter image segmentation Science Q
Acceso en línea:	https://doaj.org/article/0408dbb4d24e4d329248346e32156af1
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id	oai:doaj.org-article:0408dbb4d24e4d329248346e32156af1
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spelling	oai:doaj.org-article:0408dbb4d24e4d329248346e32156af12021-11-11T18:53:08ZGabor Filter-Based Segmentation of Railroad Radargrams for Improved Rail Track Condition Assessment: Preliminary Studies and Future Perspectives10.3390/rs132142932072-4292https://doaj.org/article/0408dbb4d24e4d329248346e32156af12021-10-01T00:00:00Zhttps://www.mdpi.com/2072-4292/13/21/4293https://doaj.org/toc/2072-4292Ground penetrating radar (GPR) has been used for several years as a non-contact and non-destructive measurement method for rail track analysis with the aim of recording the condition of ballast and substructures. As the recorded data sets typically cover a distance of many kilometers, the evaluation of these data involves considerable effort and costs. For this reason, there is an increasing need for automated support in the evaluation of GPR measurement data. This paper presents an image segmentation pipeline based on 2D Gabor filter texture analysis, which can assist users in GPR data-based track condition assessment. Gabor filtering is used to transform a radargram image (or B-scan) into a high-dimensional, multi-resolution representation. Principal component analysis (PCA) is then applied to reduce the data content to three characteristic dimensions (namely amplitude, frequency, and local scattering) to finally obtain a segmented radargram image representing different classes of relevant image structures. From these results, quantitative measures can be derived that allow experts an improved condition assessment of the rail track.Gerald ZaunerDavid GroessbacherMartin BuergerFlorian AuerGiuseppe StacconeMDPI AGarticleground penetrating radar (GPR)railwaytrack condition assessmentimage processing2D Gabor filterimage segmentationScienceQENRemote Sensing, Vol 13, Iss 4293, p 4293 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	ground penetrating radar (GPR) railway track condition assessment image processing 2D Gabor filter image segmentation Science Q
spellingShingle	ground penetrating radar (GPR) railway track condition assessment image processing 2D Gabor filter image segmentation Science Q Gerald Zauner David Groessbacher Martin Buerger Florian Auer Giuseppe Staccone Gabor Filter-Based Segmentation of Railroad Radargrams for Improved Rail Track Condition Assessment: Preliminary Studies and Future Perspectives
description	Ground penetrating radar (GPR) has been used for several years as a non-contact and non-destructive measurement method for rail track analysis with the aim of recording the condition of ballast and substructures. As the recorded data sets typically cover a distance of many kilometers, the evaluation of these data involves considerable effort and costs. For this reason, there is an increasing need for automated support in the evaluation of GPR measurement data. This paper presents an image segmentation pipeline based on 2D Gabor filter texture analysis, which can assist users in GPR data-based track condition assessment. Gabor filtering is used to transform a radargram image (or B-scan) into a high-dimensional, multi-resolution representation. Principal component analysis (PCA) is then applied to reduce the data content to three characteristic dimensions (namely amplitude, frequency, and local scattering) to finally obtain a segmented radargram image representing different classes of relevant image structures. From these results, quantitative measures can be derived that allow experts an improved condition assessment of the rail track.
format	article
author	Gerald Zauner David Groessbacher Martin Buerger Florian Auer Giuseppe Staccone
author_facet	Gerald Zauner David Groessbacher Martin Buerger Florian Auer Giuseppe Staccone
author_sort	Gerald Zauner
title	Gabor Filter-Based Segmentation of Railroad Radargrams for Improved Rail Track Condition Assessment: Preliminary Studies and Future Perspectives
title_short	Gabor Filter-Based Segmentation of Railroad Radargrams for Improved Rail Track Condition Assessment: Preliminary Studies and Future Perspectives
title_full	Gabor Filter-Based Segmentation of Railroad Radargrams for Improved Rail Track Condition Assessment: Preliminary Studies and Future Perspectives
title_fullStr	Gabor Filter-Based Segmentation of Railroad Radargrams for Improved Rail Track Condition Assessment: Preliminary Studies and Future Perspectives
title_full_unstemmed	Gabor Filter-Based Segmentation of Railroad Radargrams for Improved Rail Track Condition Assessment: Preliminary Studies and Future Perspectives
title_sort	gabor filter-based segmentation of railroad radargrams for improved rail track condition assessment: preliminary studies and future perspectives
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/0408dbb4d24e4d329248346e32156af1
work_keys_str_mv	AT geraldzauner gaborfilterbasedsegmentationofrailroadradargramsforimprovedrailtrackconditionassessmentpreliminarystudiesandfutureperspectives AT davidgroessbacher gaborfilterbasedsegmentationofrailroadradargramsforimprovedrailtrackconditionassessmentpreliminarystudiesandfutureperspectives AT martinbuerger gaborfilterbasedsegmentationofrailroadradargramsforimprovedrailtrackconditionassessmentpreliminarystudiesandfutureperspectives AT florianauer gaborfilterbasedsegmentationofrailroadradargramsforimprovedrailtrackconditionassessmentpreliminarystudiesandfutureperspectives AT giuseppestaccone gaborfilterbasedsegmentationofrailroadradargramsforimprovedrailtrackconditionassessmentpreliminarystudiesandfutureperspectives
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Gabor Filter-Based Segmentation of Railroad Radargrams for Improved Rail Track Condition Assessment: Preliminary Studies and Future Perspectives

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