A Vision-Based Method for Automatic Crack Detection in Railway Sleepers

  • Ahmad Delforouzi
  • Amir Hossein Tabatabaei
  • Muhammad Hassan Khan
  • Marcin Grzegorzek
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 578)


In this paper, a method for automatic selection and classification of the sleeper cracks is presented. This method includes three main sequential steps of image pre-processing, sleeper detection and crack detection. Two approaches including rule-based method and template matching method in the frequency domain are proposed for the sleeper detection step. We utilize adaptive threshold binarization to handle challenging crack detection under non-uniform lightening condition and hierarchical structure for the decision making step. Two unsupervised classifiers are exploited to detect the cracks. The results show that the presented method has the overall detection rate with accuracy of at least 87 percent.


Sleeper crack detection Adaptive thresholding Support vector machines Template matching 


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Ahmad Delforouzi
    • 1
  • Amir Hossein Tabatabaei
    • 1
  • Muhammad Hassan Khan
    • 1
  • Marcin Grzegorzek
    • 1
  1. 1.Pattern Recognition GroupUniversity of SiegenSiegenGermany

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