TY - GEN
T1 - Research on Bridge Crack Detection with Neural Network Based Image Processing Methods
AU - Peng, Jiafan
AU - Zhang, Shunong
AU - Peng, Dongmu
AU - Liang, Kan
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - In bridge health monitoring, the detection and localization of surface defects are highly important for health condition evaluation. Due to the limitation of manual detection, it is easier to measure those defects in a more automatic way. Machine learning is a hot topic in the recent decade, and the contribution of Artificial Neural Network (ANN) is especially remarkable, which is the most widely used models of machine learning in the image-processing field. In this paper, we will discuss two ANN-based algorithms (Back propagation (BP) and Self-Organizing Maps (SOM)) and their applications for the recognition of surface defect on images taken from bridges. Moreover, a combined network algorithm with BP and SOM is designed in order to improve the performance in crack image segmentation, and analysis over this network is carried out specifically.
AB - In bridge health monitoring, the detection and localization of surface defects are highly important for health condition evaluation. Due to the limitation of manual detection, it is easier to measure those defects in a more automatic way. Machine learning is a hot topic in the recent decade, and the contribution of Artificial Neural Network (ANN) is especially remarkable, which is the most widely used models of machine learning in the image-processing field. In this paper, we will discuss two ANN-based algorithms (Back propagation (BP) and Self-Organizing Maps (SOM)) and their applications for the recognition of surface defect on images taken from bridges. Moreover, a combined network algorithm with BP and SOM is designed in order to improve the performance in crack image segmentation, and analysis over this network is carried out specifically.
KW - Artificial neural network
KW - Bridge health monitoring
KW - Crack localization
KW - Image processing
UR - https://www.scopus.com/pages/publications/85067066454
U2 - 10.1109/ICRMS.2018.00085
DO - 10.1109/ICRMS.2018.00085
M3 - 会议稿件
AN - SCOPUS:85067066454
T3 - Proceedings - 12th International Conference on Reliability, Maintainability, and Safety, ICRMS 2018
SP - 419
EP - 428
BT - Proceedings - 12th International Conference on Reliability, Maintainability, and Safety, ICRMS 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 12th International Conference on Reliability, Maintainability, and Safety, ICRMS 2018
Y2 - 17 October 2018 through 19 October 2018
ER -