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Interpretation of ground penetrating radar dataset using normalised cross-correlation technique

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dc.contributor.authorWahab W.A.en_US
dc.contributor.authorZakaria W.Z.en_US
dc.contributor.authorOmar R.C.en_US
dc.contributor.authorRoslan R.en_US
dc.contributor.authorJaafar J.en_US
dc.contributor.authorSuldi A.M.en_US
dc.contributor.authorid56040257700en_US
dc.contributor.authorid57225366854en_US
dc.contributor.authorid35753735300en_US
dc.contributor.authorid57159693200en_US
dc.contributor.authorid55195890000en_US
dc.contributor.authorid55232478800en_US
dc.date.accessioned2023-05-29T07:23:18Z
dc.date.available2023-05-29T07:23:18Z
dc.date.issued2019
dc.description.abstractGround Penetrating Radar (GPR) is one of the latest non-destructive geophysical technology and most widely used in detecting underground utilities. GPR can detect both metal and non-metal, however, it is unable to identify the type of underground utility object. Many researchers come out with their techniques to interpret the GPR image. The current method requires experience in interpretation. Thus, in this study, a new method to detect underground utility utilizing the Normalised Cross-Correlation (NCC) template matching technique is proposed. This technique will reduce the dependency on experts to interpret the radargram, less time consuming and eventually save cost. Upon detection, the accuracy of the system is assessed. From the accuracy assessment performed, it is shown that the system provides accurate detection results for both, depth and pipe size. The Root Mean Square Error (RMSE) for the buried pipe depth obtained by using the proposed system is 0.110 m, whereas the highest percentage match obtained is 91.34%, the remaining 8.66% mismatched might be due to the soil condition, velocity or processing parameter that affected the radargram. Based on the assessment, the developed system seems capable to detect the subsurface utility if the radar image and template image used is acquired using the same antenna frequency, point interval, and similar GPR instrument. �BEIESP.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.35940/ijeat.A2675.109119
dc.identifier.epage3509
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85074608659
dc.identifier.spage3505
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85074608659&doi=10.35940%2fijeat.A2675.109119&partnerID=40&md5=222db143bee6c5e50b7e3d3f6226beb9
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/24408
dc.identifier.volume9
dc.publisherBlue Eyes Intelligence Engineering and Sciences Publicationen_US
dc.relation.ispartofAll Open Access, Bronze
dc.sourceScopus
dc.sourcetitleInternational Journal of Engineering and Advanced Technology
dc.titleInterpretation of ground penetrating radar dataset using normalised cross-correlation techniqueen_US
dc.typeArticleen_US
dspace.entity.typePublication
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