TY - JOUR
T1 - Automatic Detection of the Cracks on the Concrete Railway Sleepers
AU - Tabatabaei, Seyed Amir Hossein
AU - Delforouzi, Ahmad
AU - Khan, Muhammad Hassan
AU - Wesener, Tim
AU - Grzegorzek, Marcin
N1 - Funding Information:
This research was supported by the German Federal Ministry for Economic A®airs and Energy (BMWi) under grant number KF3411802GR4.
Publisher Copyright:
© 2019 World Scientific Publishing Company.
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2019/8/1
Y1 - 2019/8/1
N2 - A vision-based method for detecting the cracks in the concrete sleepers of the railway tracks will be introduced in this paper. The method is able to detect and partially classify the cracks of the concrete sleepers in two successive steps based on the image processing and pattern recognition techniques. The method has been implemented on the acquired image data frames followed by the analysis, experimental, comparison results and evaluation. The presented results are reasonable which indicates the goodness of the introduced method. The preliminary results of this work have been presented in [A. Delforouzi, A. H. Tabatabaei, M. H. Khan and M. Grzegorzek, A vision-based method for automatic crack detection in railway sleepers, in Kurzynski, M., Wozniak, M., Burduk, R. (eds.), Proceedings of the 10th International Conference on Computer Recognition Systems CORES 2017, Polanica Zdroj, Poland. CORES 2017. Advances in Intelligent Systems and Computing, Vol. 578 (Springer, Cham, 2018), pp. 130-139, doi: 10.1007/978-3-319-59162-9-14].
AB - A vision-based method for detecting the cracks in the concrete sleepers of the railway tracks will be introduced in this paper. The method is able to detect and partially classify the cracks of the concrete sleepers in two successive steps based on the image processing and pattern recognition techniques. The method has been implemented on the acquired image data frames followed by the analysis, experimental, comparison results and evaluation. The presented results are reasonable which indicates the goodness of the introduced method. The preliminary results of this work have been presented in [A. Delforouzi, A. H. Tabatabaei, M. H. Khan and M. Grzegorzek, A vision-based method for automatic crack detection in railway sleepers, in Kurzynski, M., Wozniak, M., Burduk, R. (eds.), Proceedings of the 10th International Conference on Computer Recognition Systems CORES 2017, Polanica Zdroj, Poland. CORES 2017. Advances in Intelligent Systems and Computing, Vol. 578 (Springer, Cham, 2018), pp. 130-139, doi: 10.1007/978-3-319-59162-9-14].
UR - http://www.scopus.com/inward/record.url?scp=85062343441&partnerID=8YFLogxK
U2 - 10.1142/S0218001419550103
DO - 10.1142/S0218001419550103
M3 - Journal articles
AN - SCOPUS:85062343441
SN - 0218-0014
VL - 33
JO - International Journal of Pattern Recognition and Artificial Intelligence
JF - International Journal of Pattern Recognition and Artificial Intelligence
IS - 9
M1 - 1955010
ER -