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Micro crack detection with Dijkstra’s shortest path algorithm

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Abstract

A package based on the free software R is presented which allows the automatic detection of micro cracks and corresponding statistical analysis of crack quantities. It uses a shortest path algorithm to detect micro cracks in situations where the cracks are surrounded by plastic deformations and where a discrimination between cracks and plastic deformations is difficult. In a first step, crack clusters are detected as connected components of pixels with values below a given threshold value. Then the crack paths are determined by Dijkstra’s algorithm as longest shortest paths through the darkest parts of the crack clusters. Linear parts of kinked paths can be identified with this. The new method was applied to over 2,000 images. Some statistical applications and a comparison with another free image tool are given.

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Authors and Affiliations

  1. Department of Mathematics, University of Kassel, 34109, Kassel, Germany

    Christina Gunkel & Alexander Stepper

  2. Department of Mathematics and Computer Science, Free University of Berlin, Arnimallee 14, 14195, Berlin, Germany

    Arne C. Müller

  3. Faculty of Statistics, University of Technology Dortmund, Vogelpothsweg 87, 44221, Dortmund, Germany

    Christine H. Müller

Authors
  1. Christina Gunkel
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  2. Alexander Stepper
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  3. Arne C. Müller
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  4. Christine H. Müller
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Correspondence to Christine H. Müller.

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Gunkel, C., Stepper, A., Müller, A.C. et al. Micro crack detection with Dijkstra’s shortest path algorithm. Machine Vision and Applications 23, 589–601 (2012). https://doi.org/10.1007/s00138-011-0324-1

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  • DOI: https://doi.org/10.1007/s00138-011-0324-1

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