contributor author | Yi-Chang (James) Tsai | |
contributor author | Anirban Chatterjee | |
date accessioned | 2017-12-30T13:05:52Z | |
date available | 2017-12-30T13:05:52Z | |
date issued | 2018 | |
identifier other | %28ASCE%29CP.1943-5487.0000726.pdf | |
identifier uri | http://138.201.223.254:8080/yetl1/handle/yetl/4245557 | |
description abstract | Potholes 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. | |
publisher | American Society of Civil Engineers | |
title | Pothole Detection and Classification Using 3D Technology and Watershed Method | |
type | Journal Paper | |
journal volume | 32 | |
journal issue | 2 | |
journal title | Journal of Computing in Civil Engineering | |
identifier doi | 10.1061/(ASCE)CP.1943-5487.0000726 | |
page | 04017078 | |
tree | Journal of Computing in Civil Engineering:;2018:;Volume ( 032 ):;issue: 002 | |
contenttype | Fulltext | |