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Automatic Detection of the Cracks on the Concrete Railway Sleepers

Seyed Amir Hossein Tabatabaei*, Ahmad Delforouzi, Muhammad Hassan Khan, Tim Wesener, Marcin Grzegorzek

*Korrespondierende/r Autor/-in für diese Arbeit

Abstract

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].

OriginalspracheEnglisch
Aufsatznummer1955010
ZeitschriftInternational Journal of Pattern Recognition and Artificial Intelligence
Jahrgang33
Ausgabenummer9
ISSN0218-0014
DOIs
PublikationsstatusVeröffentlicht - 01.08.2019

Fördermittel

This research was supported by the German Federal Ministry for Economic A®airs and Energy (BMWi) under grant number KF3411802GR4.

UN SDGs

Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung

  1. SDG 3 – Gesundheit und Wohlergehen
    SDG 3 – Gesundheit und Wohlergehen
  2. SDG 9 – Industrie, Innovation und Infrastruktur
    SDG 9 – Industrie, Innovation und Infrastruktur

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