Maximilian Klockmann, Marco Filax, Frank Ortmeier, Martin Reiß: On the Similarities of Fingerprints and Railroad Tracks: Using Minutiae Detection Algorithms to digitize Track Plans.. In: 13th IAPR Workshop on Document Analysis Systems (DAS), 2018.

Abstract

The complete track system of Germany covers more than 42.000 kilometers - some built before 1970. As a consequence, technical drawings are typical of manual origin. Newer plans are generated in a computer-aided way but remain drawings in the sense that semantics are not captured in the electronic files themselves. The engineer decides the meaning of a symbol while viewing the document. For project realization (e.g., engineering of some interlocking system), these plans are digitized manually into some machine interpretable format.
In this paper, we propose an approach to digitize track layouts (semi-)automatically. We use fingerprint recognition techniques to digitize manually created track plans efficiently. At first, we detect tracks by detecting line endings and bifurcations.
Secondly, we eliminate false candidates and irregularities. Finally, we translate the resulting graph into an interchangeable format RailML.
We evaluate our method by comparing our results with different track plans. Our results indicate that the proposed method is a promising candidate, reducing the effort of digitization.

    BibTeX (Download)

    @inproceedings{klock18,
    title = {On the Similarities of Fingerprints and Railroad Tracks: Using Minutiae Detection Algorithms to digitize Track Plans.},
    author = {Maximilian Klockmann and Marco Filax and Frank Ortmeier and Martin Rei\ss},
    year  = {2018},
    date = {2018-01-01},
    booktitle = {13th IAPR Workshop on Document Analysis Systems (DAS)},
    abstract = {The complete track system of Germany covers more than 42.000 kilometers - some built before 1970. As a consequence, technical drawings are typical of manual origin. Newer plans are generated in a computer-aided way but remain drawings in the sense that semantics are not captured in the electronic files themselves. The engineer decides the meaning of a symbol while viewing the document. For project realization (e.g., engineering of some interlocking system), these plans are digitized manually into some machine interpretable format.
    In this paper, we propose an approach to digitize track layouts (semi-)automatically. We use fingerprint recognition techniques to digitize manually created track plans efficiently. At first, we detect tracks by detecting line endings and bifurcations. 
    Secondly, we eliminate false candidates and irregularities. Finally, we translate the resulting graph into an interchangeable format RailML. 
    We evaluate our method by comparing our results with different track plans. Our results indicate that the proposed method is a promising candidate, reducing the effort of digitization. },
    keywords = {Digitization, Information Extraction, Minutiae Detection, rack Layout Analysis},
    pubstate = {published},
    tppubtype = {inproceedings}
    }