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dc.contributor.authorYi-Chang (James) Tsai
dc.contributor.authorAnirban Chatterjee
dc.date.accessioned2017-12-30T13:05:52Z
dc.date.available2017-12-30T13:05:52Z
dc.date.issued2018
dc.identifier.other%28ASCE%29CP.1943-5487.0000726.pdf
dc.identifier.urihttp://138.201.223.254:8080/yetl1/handle/yetl/4245557
dc.description.abstractPotholes are one of the roadway distresses that negatively impact roadway safety. With emerging sensing technology, three-dimensional (3D) pavement data, derived using 3D laser technology, have become available for detecting cracking and rutting. This paper presents a pothole detection method using 3D pavement data and a watershed method. Tests using the 3D data collected on 10th Street, Atlanta, Georgia and 6 mi of roadway on U.S. 80, Savannah, Georgia, has shown a 94.97% accuracy, 90.80% precision, and 98.75% recall. It has been demonstrated that the proposed method is promising for pothole detection and can provide a reliable method for pothole detection, especially when 3D pavement data have been collected for crack detection and already available.
dc.publisherAmerican Society of Civil Engineers
dc.titlePothole Detection and Classification Using 3D Technology and Watershed Method
dc.typeJournal Paper
dc.journal.volume32
dc.journal.issue2
dc.journal.titleJournal of Computing in Civil Engineering
dc.identifier.doi10.1061/(ASCE)CP.1943-5487.0000726
dc.page04017078
dc.treeJournal of Computing in Civil Engineering:;2018:;Volume ( 032 ):;issue: 002
dc.contenttypeFulltext


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