Service interruption on Monday 11 July from 12:30 to 13:00: all the sites of the CCSD (HAL, Epiciences, SciencesConf, AureHAL) will be inaccessible (network hardware connection).
Skip to Main content Skip to Navigation
Conference papers

The Classification of Pavement Crack Image Based on Beamlet Algorithm

Abstract : Pavement distress, the various defects such as holes and cracks, represent a significant engineering and economic concern. This paper based on Beamlet algorithm using MATLAB software to process the pavement crack images and classify the different cracks into four types: horizontal, vertical, alligator, and block types. Experiment results show that the proposed method can effectively detect and classify of the pavement cracks with a high success rate, in which transverse crack and longitudinal crack detection rate reach to 100%, and alligator crack and block crack reach more than 85%.
Document type :
Conference papers
Complete list of metadata

Cited literature [6 references]  Display  Hide  Download

https://hal.inria.fr/hal-01220821
Contributor : Hal Ifip Connect in order to contact the contributor
Submitted on : Tuesday, October 27, 2015 - 8:24:18 AM
Last modification on : Wednesday, January 17, 2018 - 10:45:36 AM
Long-term archiving on: : Thursday, January 28, 2016 - 10:20:38 AM

File

978-3-642-54341-8_13_Chapter.p...
Files produced by the author(s)

Licence


Distributed under a Creative Commons Attribution 4.0 International License

Identifiers

Citation

Aiguo Ouyang, Qin Dong, yaping Wang, yande Liu. The Classification of Pavement Crack Image Based on Beamlet Algorithm. 7th International Conference on Computer and Computing Technologies in Agriculture (CCTA), Sep 2013, Beijing, China. pp.129-137, ⟨10.1007/978-3-642-54341-8_13⟩. ⟨hal-01220821⟩

Share

Metrics

Record views

102

Files downloads

88