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Automatic Watermeter Reading in Presence of Highly Deformed Digits

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Computer Analysis of Images and Patterns (CAIP 2021)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 13053))

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Abstract

The task we face in this paper is to automate the reading of watermeters as can be found in large apartment houses. Typically water passes through such watermeters, so that one faces a wide range of challenges caused by water as the medium where the digits are positioned. One of the main obstacles is given by the frequently produced bubbles inside the watermeter that deform the digits. To overcome this problem, we propose the construction of a novel data set that resembles the watermeter digits with a focus on their deformations by bubbles. We report on promising experimental recognition results, based on a deep and recurrent network architecture performed on our data set.

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Acknowledgements

Authors would like to thank Meine-Energie GmbH and the financial support from Zentrale Innovationsprogramm Mittelstand (ZIM) over Arbeitsgemeinschaft industrieller Forschungsvereinigungen (AiF).

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Authors and Affiliations

  1. Institute of Mathematics, Brandenburg Technical University, Platz der Deutschen Einheit 1, 03046, Cottbus, Germany

    Ashkan Mansouri Yarahmadi & Michael Breuß

Authors
  1. Ashkan Mansouri Yarahmadi
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  2. Michael Breuß
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Corresponding author

Correspondence to Ashkan Mansouri Yarahmadi .

Editor information

Editors and Affiliations

  1. Cyprus University of Technology, Limassol, Cyprus

    Nicolas Tsapatsoulis

  2. University of Cyprus, Nicosia, Cyprus

    Andreas Panayides

  3. University of Cyprus, Nicosia, Cyprus

    Theo Theocharides

  4. Cyprus University of Technology, Limassol, Cyprus

    Andreas Lanitis

  5. University of Cyprus, Nicosia, Cyprus

    Constantinos Pattichis

  6. University of Salerno, Salerno, Italy

    Mario Vento

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Yarahmadi, A.M., Breuß, M. (2021). Automatic Watermeter Reading in Presence of Highly Deformed Digits. In: Tsapatsoulis, N., Panayides, A., Theocharides, T., Lanitis, A., Pattichis, C., Vento, M. (eds) Computer Analysis of Images and Patterns. CAIP 2021. Lecture Notes in Computer Science(), vol 13053. Springer, Cham. https://doi.org/10.1007/978-3-030-89131-2_14

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  • DOI: https://doi.org/10.1007/978-3-030-89131-2_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-89130-5

  • Online ISBN: 978-3-030-89131-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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