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Image-Based Recognition of Braille Using Neural Networks on Mobile Devices

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Part of the Lecture Notes in Computer Science book series (LNISA,volume 12376)

Abstract

Braille documents are part of the collaboration with blind people. To overcome the problem of learning Braille as a sighted person, a technical solution for reading Braille would be beneficial. Thus, a mobile and easy-to-use system is needed for every day situations. Since it should be a mobile system, the environment cannot be controlled, which requires modern computer vision algorithms. Therefore, we present a mobile Optical Braille Recognition system using state-of-the-art deep learning implemented as an app and server application.

Keywords

  • Optical Braille Recognition
  • Deep learning
  • Mobile devices

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Notes

  1. 1.

    Emfuse, EmBraille from Viewplus and Everest from Index Braille.

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Correspondence to Thorsten Schwarz .

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Baumgärtner, C., Schwarz, T., Stiefelhagen, R. (2020). Image-Based Recognition of Braille Using Neural Networks on Mobile Devices. In: Miesenberger, K., Manduchi, R., Covarrubias Rodriguez, M., Peňáz, P. (eds) Computers Helping People with Special Needs. ICCHP 2020. Lecture Notes in Computer Science(), vol 12376. Springer, Cham. https://doi.org/10.1007/978-3-030-58796-3_41

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  • DOI: https://doi.org/10.1007/978-3-030-58796-3_41

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-58795-6

  • Online ISBN: 978-3-030-58796-3

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