Long-distance precision inspection method for bridge cracks with image processing
Authors:
- Gang LiGLGang Li
- Shuanhai HeSHShuanhai He
- Yongfeng JuYJYongfeng Ju
- Kai DuKDKai Du
- 1 May 2014
- journal article
- Published by Elsevier in Automation in Construction
- Vol. 41, 83-95
Abstract
No abstract availableFunding Information
- Science and Technology Bureau of Xi'an industrial application technology R & D projects (CXY1350(8))
- Chang'an University of Central universities basic research and operating expenses of special funds project (2013G1321039)
This publication has 15 references indexed in Scilit:
- CrackTree: Automatic crack detection from pavement imagesPattern Recognition Letters, 2012
- Dynamic testing of a damaged bridgeMechanical Systems and Signal Processing, 2011
- Bridge inspection robot system with machine visionAutomation in Construction, 2009
- Auto inspection system using a mobile robot for detecting concrete cracks in a tunnelAutomation in Construction, 2007
- Segmentation of Pipe Images for Crack Detection in Buried SewersComputer-Aided Civil and Infrastructure Engineering, 2006
- Improved Image Analysis for Evaluating Concrete DamageJournal of Computing in Civil Engineering, 2006
- Wavelet-based crack identification of bridge beam from operational deflection time historyInternational Journal of Solids and Structures, 2006
- Automated detection of cracks in buried concrete pipe imagesAutomation in Construction, 2006
- Color image segmentation based on adaptive local thresholdsImage and Vision Computing, 2005
- Analysis of Edge-Detection Techniques for Crack Identification in BridgesJournal of Computing in Civil Engineering, 2003