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contributor authorYi-Chang (James) Tsai
contributor authorAnirban Chatterjee
date accessioned2017-12-30T13:05:52Z
date available2017-12-30T13:05:52Z
date issued2018
identifier other%28ASCE%29CP.1943-5487.0000726.pdf
identifier urihttp://138.201.223.254:8080/yetl1/handle/yetl/4245557
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.
publisherAmerican Society of Civil Engineers
titlePothole Detection and Classification Using 3D Technology and Watershed Method
typeJournal Paper
journal volume32
journal issue2
journal titleJournal of Computing in Civil Engineering
identifier doi10.1061/(ASCE)CP.1943-5487.0000726
page04017078
treeJournal of Computing in Civil Engineering:;2018:;Volume ( 032 ):;issue: 002
contenttypeFulltext


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