Proceedings of the 2nd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2017)

Application Research on Convolution Neural Network for Bridge Crack Detection

Authors
Jinghang Cen, Jiankang Zhao, Xuan Xia, Chuanqi Liu
Corresponding Author
Jinghang Cen
Available Online July 2016.
DOI
https://doi.org/10.2991/iccia-17.2017.24How to use a DOI?
Keywords
image processing, bridge crack, detection, convolution neural network
Abstract
The bridge crack detection still relies on human visual measurement nowadays, which means low efficiency and high cost. In view to this situation, the convolution neural network(CNN) was introduced into bridge crack detection to improve the efficiency and reduce the error caused by manual work. In this paper, we designed a recognition algorithm based on convolution neural network, which can directly input the crack images obtained by UAV, avoids the complicated feature extraction pre-processing used in the traditional image processing. Basis on that, this paper puts forward a algorithm of image filter window with variable size control, and also carries on the experiments to set the threshold value of the length of the connected domain. Finally, an intelligent recognition scheme is obtained, which is suitable for crack recognition, and the recognition rate is over 95%, means that it has a good application prospect.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Proceedings
2nd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2017)
Part of series
Advances in Computer Science Research
Publication Date
July 2016
ISBN
978-94-6252-361-6
ISSN
2352-538X
DOI
https://doi.org/10.2991/iccia-17.2017.24How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Jinghang Cen
AU  - Jiankang Zhao
AU  - Xuan Xia
AU  - Chuanqi Liu
PY  - 2016/07
DA  - 2016/07
TI  - Application Research on Convolution Neural Network for Bridge Crack Detection
BT  - 2nd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2017)
PB  - Atlantis Press
SP  - 150
EP  - 156
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccia-17.2017.24
DO  - https://doi.org/10.2991/iccia-17.2017.24
ID  - Cen2016/07
ER  -